Job Board

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Multiple PhD Positions in Foundations of Deep Learning and Computer Vision in Computational Pathology
We invite applications for several PhD positions in the area of deep learning, computer vision and computational pathology. We seek candidates with research interests related to the development of computational approaches to analyze and model medical images in histopathology. The expected candidates will conduct research on deep learning and computer vision topics such as multi-label representation learning, deep metric learning, knowledge distillation, deep learning optimization, cancer representation, cancer diagnosis, and generative models. The students will be supervised by Prof. Mahdi S. Hosseini and will earn a doctorate degree in Computer Science from Concordia University, Montreal, Canada. The positions are funded and a competitive financial support will be provided to qualified candidates. More info can be found from LinkeIn.

MSc Position in Foundations of Deep Learning and Computer Vision in Medical Imaging
We invite applications in a MSc position on deep learning and computer vision topics focused on medical imaging applications. We seek candidates with highly qualified background with research interests related to the development of computational approaches to analyze and model medical images. The expected candidate will conduct research on deep learning and computer vision topics such as multi-label representation learning, deep metric learning, knowledge distillation, deep learning optimization, cancer representation, cancer diagnosis, and generative models. The students will be supervised in collaboration by Prof. Mahdi S. Hosseini and Prof. Hassan Rivaz and will earn a master’s degree in Computer Science from Concordia University, Montreal, Canada. A competitive financial package will be provided for qualified candidate. More info can be found from LinkedIn.

Fully Funded PhD Position in Generative Modelling for 3D Computer Vision
Imperial College London is looking for a PhD student working on generatively modelling 3D data, as part of the Geometric Machine Learning and 3D Vision Group headed by Tolga Birdal. Today, deep neural networks can generate images almost indistinguishable from real captures. Yet, for data defined on other domains such as point clouds, meshes or graphs, the same level of performance is not attained. To date, generatively modelling 3D geometric data has remained a notorious challenge subscribing to no de-facto consensus. This dearth of prosperous generative models that can model the underlying distribution of the 3D data and that can generate point sets resembling realistic shapes, has become an obstacle in the way of successful unsupervised learning on 3D domains, blocking the way to geometric AI revolution in three or higher dimensional domains. The successful PhD candidate leading this effort will combat the aforementioned limitation by leveraging the recent theoretical advances in deep learning as well as the emerging generative models driven by statistical mechanics (e.g. diffusion models) to devise and deploy deep geometric neural generative models suited to the nature of 3D data. The following qualifications are expected:  Experience in Python, machine learning – Ability to lead independent research. Experience in geometric data processing. Experience in graph or point cloud networks is a plus.
University: Imperial College London (
Contact: Tolga Birdal []
Location: London / UK

Fully Funded PhD Position in Geometric and Topological Machine Learning
Geometric Machine Learning and 3D Vision Group recently formed by Tolga Birdal within Imperial College London is seeking PhD students to work on the edge of geometric machine learning. In particular, we expect the candidates whose interests are related to topological deep learning and geometric learning. The focus of this project is higher order deep models defined on data supported on higher order domains such as simplicial or cellular complexes. Such models that can naturally incorporate higher order information are useful in a range of applications from cloth modelling to drug discovery.  The successful candidate will tackle theoretical analysis of higher-order neural networks while implementing these models for applications in 3d computer vision. This work will be highly collaborative, and the following qualifications are required:  Experience in Python, machine learning – Ability to lead independent research. Experience in geometric data processing. Experience in Graph and higher-order (simplicial/cellular/hypergraphs) neural networks is a plus.
University: Imperial College London (
Contact: Tolga Birdal []
Location: London / UK

UCSF Genentech Postdoctoral Fellow
The Keiser Lab at UCSF in collaboration with the Discovery Chemistry group at Genentech is looking for highly motivated postdoctoral candidates with a background in machine learning, computational chemistry, chemical informatics, or related fields. The candidate would work to explore chemical space through the lens of machine learning models. The project involves the design and testing of algorithms to map and quantify chemical latent space for use in drug discovery. The postdoc’s primary appointment would be at UCSF but they will be closely integrated with Genentech collaborators.
Qualifications: Python expertise required. PyTorch experience preferred. Desired, but not strictly required, skills include experience with pandas, sklearn, dask, slurm, and GPU clusters. Expertise with massive and/or distributed dataset analysis is a plus. Computational chemistry, drug discovery, medicinal chemistry, or demonstrably related domain expertise is also required. A productive track record with at least one first-author publication is required. We seek a driven individual who will hit the ground running, lead her/his research independently, and communicate frequently and clearly to the field and industry partners.
Environment: Just north of Silicon Valley, the Keiser lab’s location at UCSF Mission Bay directly adjoins SoMa district and the heart of SF’s tech and artificial intelligence startup scene. Our collaborators at the nearby Genentech South San Francisco campus are committed to discover effective medicines for unmet medical needs through the application of state-of-the-art drug discovery technologies.
How to apply: Interested candidates should submit a CV and arrange that three letters of reference be sent directly to Please reference “postdoc-dnn-ucsf-genentech”.

PostDoc position on Explainable AI for Unmanned Aerial Vehicles
In this era of big data and artificial intelligence (AI), spatial information collected through remote sensing or earth observation is essential for promoting sustainable development. Unmanned aerial vehicles (UAVs), also known as RPAS or drones, can collect very detailed imagery and photogrammetric point clouds. Machine learning and deep learning methods (e.g. CNNs, FCNs) can then automatically process this data into spatial information. Indeed this combination of spatial detail provide by UAVs with automated data processing shows great promise to support sustainable development in Lower-Middle Income Countries (LMICs), particularly in applications such as automated building detection, slum mapping, and disaster risk management. However, there is also an increasing societal concern regarding Ethical AI or AI for good. There are concerns on how to explain and interpret the “black-box” results so they can be trusted and better utilized for decision-making. UNESCO is drafting Recommendations on the Ethics of Artificial Intelligence and the European Commission is drafting a binding Regulation for Artificial Intelligence. These guidelines emphasize the importance of embedding explainability and interpretability into algorithms. And yet, despite research in the fields of FATML and XAI, there is little knowledge on best practices for explaining the results of algorithms in the geospatial domain. To address this gap there is a vacant full-time position for a researcher in explainable AI. The successful applicant will integrate explainability techniques into deep learning workflows for classifying UAV imagery. The precise tasks under this theme will be discussed with the applicant and can be flexible to the applicant’s expertise and interest.
More information can be found here: Job location: Enschede, the Netherlands; Company: University of Twente – Faculty ITC; Contact Information: Caroline Gevaert (

Assistant Professor (tenure track) in Machine Learning with focus on remote sensing
We are looking for an assistant professor (tenure track) in machine learning with focus on remote sensing, addressing method research on spatial modelling and surround sensing. The employment will be based at
at the Computer Vision Laboratory, Linköping University in Sweden (, and will be part of the strategic research area within IT and mobile communication, ELLIIT ( Deadline: 21 September CEST. For further details and sending your application please visit

ML Research Scientist at NT Parameter Lab GmbH in Tübingen, Germany
We are building a new group of ambitious, independent-minded researchers to tackle the trustworthiness of billion-scale ML models. The team will work on the in-house large language models and large-scale multi-modal models at Naver, an internet company in South Korea. As an independent researcher, you will be given the autonomy to define and solve problems in billion-scale models. You will present your results through academic publications and tech transfers. You will build unique expertise in dealing with billion-scale models. More information at Job location: Tübingen, Germany; Contact information:

3 year PhD Position on Deep interactive control of virtual character’s motion based on separating identity, motion and style @ Inria Rennes, France
Inria and InterDigital recently launched the lab dedicated to research on Artificial Intelligence (AI) for the e-society. Within this collaborative framework, we recently initiated the project which focuses on representation formats for digital avatars and their behavior in a digital and responsive environment, and are looking for several PhDs and post-docs to work on the user representation within the future metaverse. This PhD position will focus on exploring, proposing and evaluating novel solutions to represent both body shape and movements in a compact latent representation. This representation aims at simplifying the adaptation of the shape (identity) of a user, or/and his motion, and/or the style of both his shape and motion (such as transferring the user’s moving shape to a fictional character with different properties and style). More details:

Postdoc positions at Osaka University
Institute for Databilisty Science, Osaka University, is opening a few postdoctoral positions for computer vision and pattern recognition researchers. We are committed to interdisciplinary projects with collaborating researchers in various fields such as medical, humanity, and physics using computer vision and machine learning techniques. Some example projects can be found at: Our main focus is to contribute to the computer vision and machine learning communities in the course of such projects, so we are encouraging all our researchers/students to submit papers to top conferences like CVPR, ICCV, ECCV, and ICLR. We welcome researchers who can lead individual projects from the very beginning of their lifecycle (i.e., project proposals).
Application process: Please send your CV to, and we will invite you to an interview after screening.
Prof. Hajime Nagahara is at the ECCV venue for you to have an unofficial chat so that you can know more about us. Feel free to send an email to to make an appointment.

Fully-Funded Open PhD and PostDoc Positions in 3D Computer Vision and Continual Learning
The Computer Vision and Machine Perception research lab at Saarland University has openings for funded PhD and PostDoc positions in in 3D Computer Vision and Continual Learning. The goal of your project will be to advance state-of-the-art machine perception algorithms by lifting the representation to 3D and enabling the systems to increase their knowledge from continuously incoming unlabeled data. To this end, you will be developing deep learning-based models that can reason about their own knowledge and combine those models with state-of-the-art 3D reconstruction techniques. Your work will involve 3D reconstruction, physical light transport models, uncertainty estimation and continual learning and connect to natural language processing, reinforcement learning and fundamental research. The research is highly relevant for the future of AI and the practical use of your research will be for 3D scene understanding, contextual AI, virtual shopping and visual search. Saarland University is one of the leading locations for computer science in Germany and Europe. The Computer Vision and Machine Perception research lab is headed by Eddy Ilg with close ties to MPI Saarbrücken and to Meta. Please see for more information.

Open Phd Position at RSiM, TU Berlin
We are looking for a highly motivated Phd researcher who is interested in performing cutting-edge research on machine learning models for organic agriculture monitoring. Starting from the analysis of the start-of-the-art models, the successful candidate will focus on the design and development of novel semantic segmentation models that tackle research problems related to domain adaptation and generalization, self-supervised learning, weakly-supervised learning, multimodal learning, learning with imbalanced/few data or with noisy labeled data, spatiotemporal fusion. This research activity is a part of the project ‘Earth Observation and Artificial Intelligence for monitoring organic agriculture’ funded by the German Federal Ministry for Economic Affairs and Climate Action. For details, please click here.

Research Scientist / Engineer for Reinforcement Learning / Planning position at Robert Bosch Technologies Israel
Robert Bosch Technologies Israel Ltd is a subsidiary of Robert Bosch GmbH in Israel, focusing on Artificial Intelligence research and Open Innovation. Our research group in Haifa focuses on Reinforcement Learning, Deep Learning, Robotics, Off-Road Autonomous Vehicles, and Planning. Visit the lab website:

Job Description:
– Research and development of novel reinforcement learning algorithms for self-driving off-road vehicles or manipulation robotics
– Focus on development of scalable RL algorithms that work reliably for real world applications
– In particular, focus on model-based RL for physical systems and Deep RL for complex decision problems.
– Creating original research and publishing at top Machine Learning conferences such as NeurIPS, ICML, ICLR, IROS, ICRA, ICCV, ECCV, CVPR, etc.
– Transfer of state-of-the-art research results to Bosch applications
– Technical discussions and creation of new ideas within the existing Reinforcement Learning research team
More details on this job offer can be found at this link.

Internship at AI Research Team position at Robert Bosch Technologies Israel
Do you care about impact on people? Do you want to publish your work in top tier-1 conferences?
Bosch Center for Artificial Intelligence in Israel is a unique place that researches and implements cutting edge technologies for manufacturing, automotive, robotics, and industrial applications. We are looking for Reinforcement Learning, Computer Vision, Planning, and Control & Machine Learning experts to various projects. If such things interest you, then Bosch Israel is looking forward for your application!

Job Description:
– Duration: 4-11 Months
– Create something new: As a research intern scientist you will conduct excellent research on real-world project. The results will be published at the leading AI venues and transferred for implementation in Bosch products.
– Strong SW engineering capabilities: High proficiency in Python, Deep Learning frameworks, and CV methods in general.

– Currently pursuing (or completed) a PhD or MsC in CS / EE / IE / ME or related faculties
– Pursuing a thesis in one of the following areas: Reinforcement Learning, Computer Vision, Autonomous Vehicles, Robotics
– Self-confident and responsible team player with excellent communication skills
– Initiative, highly motivated and motivating character for the team and partners

Additional Information
Bosch AI site:, Haifa team site:

Further references / papers created during an internship at BCAI (Bosch Centre for Artificial Intelligence):
S. Di Castro Shashua, S. Mannor, D. Di Castro. “Sim and Real: Better Together”. NeurIPS 2021.
J. Oren, C. Ross, M. Lefarov, F. Richter, A. Taitler, Z. Feldman, D. Di Castro, C. Daniel. “SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems”. SOCS, 2021.
O. Spector, D. Di Castro. “InsertionNet – A Scalable Solution for Insertion”. IROS 2021, RAL.
E. Kosman, D. Di Castro. Vision-Guided Forecasting–Visual Context for Multi-Horizon Time Series Forecasting. arXiv preprint arXiv:2107.12674, 2021. Presentation
Botach, Y. Feldman, Y. Miron, Y. Shapiro, D. Di Castro. BIDCD-Bosch Industrial Depth Completion Dataset. arXiv preprint arXiv:2108.04706

Multiple positions in Computer Vision for Earth Observation in Paris, France
The Center for Studies and Research in Computer Science and Communication (CEDRIC) has multiple open positions at various levels (PhD/postdoc/research engineer) in the context of the MAGE project. We are looking for people willing to dive into deeep learning for computer vision with applications to Earth Observation. We are located in the
heart of Paris, in the prestigious Conservatoire national des arts et métiers (Cnam). In short, the positions are:
– Fully funded PhD position (3 years) on self/semi-supervised learning for Earth Observation :
– Postdoc (1 year) on domain adaptation and/or generative models for EO
– Research engineer (1 year contract) on procedural generation of cities
See more details on the project website:

ELBE Postdoctoral Fellows in Computer Science
The Center for Systems Biology Dresden (CSBD) provides fully funded, 2-3 year positions in an international and crossdisciplinary research environment. ELBE postdoctoral fellows benefit from close collaborations with scientists at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), the Max Planck Institute for the Physics of Complex Systems (MPI-PKS), and the Faculty of Computer Science of Technische Universität Dresden (TUD), in a stimulating and inspiring atmosphere. Further information can be accessed by visiting our webpage at
The ELBE program seeks outstanding external candidates who are passionate about bringing new ideas, concepts, or systems to the CSBD. ELBE postdoctoral fellows pursue an interdisciplinary research project in collaboration with members of the CSBD. They develop and use computational approaches (e.g. numerical simulation, bioinformatics, machine learning, computer vision, AR/VR computer graphics, datadriven modeling) to study biological systems in close collaboration with experimental groups. Ideal candidates should have a PhD in computer science or mathematics, with a strong interest in working in a cross-disciplinary life-science environment. For details about the application procedure, please visit our website
Selection of ELBE fellows is based on scientific merit with two application cycles per year. Short-listed candidates should be prepared to join a selection symposium held on 8 November, 2022, either virtually or in Dresden, depending on the global Covid19 situation. Travel costs will be covered by the CSBD. Deadline for applications is 8 September, 2022.

Postdoc and PhD positions on interpretable species recognition
We are looking for a postdoc and a PhD to work on interpretable computer vision methods for species identification by making explicit use of morphological traits. For the full decription:
Location: Montpellier, France.
Institution: Inria.

Multiple Postdoc and PhD positions at HKU
The Department of Computer Science at The University of Hong Kong (HKU) has multiple Ph.D. students (starting Spring/Fall 2023) and Postdocs positions with Prof. Dong Xu ( in the areas of computer vision and machine learning. The postdoc positions are expected to last for up to three years with flexible starting date. The ideal candidate is expected to have a Ph.D. in CS/ECE/EE on a topic related to computer vision, multimedia and machine learning. For outstanding postdoc applicants whose applications are submitted before 5 September 2022, they can be recommended to compete for the HKU Presidential Research Assistant Professorship (, for which each award will be for three years with the basic annual salary ranging from HK$549,600 to HK$600,000 (approximately US$70,000 to US$77,000) plus 15% contract gratuity. For outstanding PhD applicants whose applications are submitted before 30 September 2022, they can be recommended to compete for the Hong Kong PhD Fellowship (, which provides an annual stipend of HK$325,200 (approximately US$41,690) and a conference and research-related travel allowance of HK$13,600 (approximately US$1,740) per year for each awardee for a period up to three years. For application, please email a CV/resume to Prof. Dong Xu (

Research Engineer in Autonomous Driving
Applications are invited from researchers in autonomous driving perception and computer vision. Candidates will work in Shanghai AI Lab. These positions are available immediately and offer a competitive salary. It also offers the possibility of collaboration-internships with research companies and institutions such as MMLab and Huawei. We are looking for highly motivated candidates interested in conducting research on the frontiers of deep learning algorithms for autonomous driving, with a particular focus on deep learning models for bev perception, sensor fusion, and perceptual decision integration. Potential applicants should have the following qualifications:
– A strong academic record with an excellent MS/PhD in computer science, artificial intelligence or vehicle engineering, preferably with expertise in one or more of the following areas: deep learning, computer vision, pattern recognition, artificial intelligence.
– Strong Coding skills, good C++/Python coding habits, ability to quickly design and execute experiments, validate ideas, and have the learning ability to be able to support full-stack development efforts.
– Good programming skills in Python, with knowledge of deep learning frameworks. Proficiency in at least one of the frameworks such as PyTorch, TensorFlow, Caffe, etc.
– Background in projects and research related to the field of autonomous driving is preferred.
– Strong publication record in major conferences or journals on computer vision and deep learning is preferred.
Application Process: For consideration, please send your resume to Eric :; For more information see:

Postdoc and PhD Positions at ETS Montreal
Applications are invited for post-doctoral researchers and Ph.D. students in deep learning applied to affective computing (eHealth), video recognition, and medical image processing. Candidates will work at the Laboratory of imaging, vision, and artificial intelligence (LIVIA), ETS Montreal. These funded positions are available immediately and offer a competitive salary. It also offers a possibility for collaborations-internships with top research companies and institutions in Montreal and abroad. We are looking for highly motivated candidates who are interested in performing cutting-edge research on machine learning algorithms, with a particular focus on deep learning models (e.g, auto-encoders, convolutional and recurrent neural networks) for domain adaptation, information fusion, and weakly-supervised learning. Prospective applicants should have the following profile:
– strong academic record with an outstanding M.Sc./Ph.D. in computer science, applied mathematics, or electrical engineering, preferably with expertise in one or more of the following areas: machine learning, computer vision, pattern recognition, artificial intelligence;
– good mathematical background;
– very good knowledge of English
– good programming skills in languages such as Python, with knowledge of deep learning frameworks;
– strong publication record in major conferences or journals in computer vision and machine learning.
Application process: For consideration, please send your CV, research statement, names and contact details of two references, transcripts, a link to your Ph.D. thesis, as well as relevant publications to Eric Granger:

Doctoral student positions in machine learning, computer vision and AI in Helsinki, Finland
There are several open positions for doctoral students and postdocs available at the Finnish Center of Artificial Intelligence in Helsinki, Finland. The positions cover several topics in machine learning, computer vision and artificial intelligence. For more information see: The application deadline is August 28.

Postdoc on Uncertainty and Deep Learning at ENSTA Paris
The U2iS laboratory of ENSTA Paris at Institut Polytechnique de Paris is looking for a motivated and enthusiastic young researcher to work on 3D pose estimation and uncertainty. Founded in 1741 ENSTA Paris is the oldest “Grande Ecole” in France and is located in Palaiseau in the south of Paris. We seek a research post-doc interested in uncertainty quantification. Deep Neural networks are increasingly overconfident and it is essential to be able to quantify their uncertainty. The candidate should have basic knowledge of Deep Learning. Computer science/ or mathematician profiles are also welcome to apply. If you are interested, please contact gianni.franchi at See also:

Research Engineer in Synthetic Data Generation and Augmentation
At Bosch Center for AI we conduct research on state-of-the-art deep generative models that are used to enable real-world Bosch systems to be data-efficient. We are looking for a research engineer to support us both in academic research activities and in transferring those results to real-world systems. The goal of this position is to develop new learning algorithms for generating better training datasets, making algorithms robust, reliable, and safe when learning even from limited/biased datasets. In particular, the focusing is on the use of generative models for data augmentation: generation of synthetic data using both computer graphics and image-synthesis with generative models (i.e., VAE, GANs, diffusion models), as well as techniques for domain transfer. Concretely, your tasks will include:
– Develop and prototype novel approaches for synthetic data generation and augmentation using deep generative models and computer graphics techniques, and apply them on real-world problems in collaboration with our partners from Bosch business units.
– Support the rapid transfer from research prototypes into products. Participate and drive the development of our software architecture for deep learning research and application.
– Ensure high coding quality for research assets to facilitate transfer to industrialization partners.
– Be part of applying our data synthesis tools to a large variety of applications within Bosch.
Location: Renningen/Tuebingen, Germany – More information:

PhD position in “3D Reconstruction of Humans in Interaction from Images” @ UvA, Amsterdam
Do you want to help computers see, understand, and assist us, humans, in our everyday life? Humans constantly interact with objects, spaces, and other humans to perform tasks. This is reflected in the photos and videos that we upload on Facebook, Instagram, YouTube, or that we capture through smart glasses (Microsoft’s HoloLens, Meta’s Aria). Our long-term goal is to develop human-centered AI that accurately perceives humans from images while performing tasks and assists them in these. Among others, this project involves challenges such as: reconstructing deformable 3D human bodies, hands, and objects from single-/multi-view images, dealing with strong occlusions during human-object interactions, representing the spatial relations and semantics of such interactions, accounting for the lack of training data, and extending 3D reconstruction over time (4D). Do you aspire to conduct internationally visible research, and to do so in one of the world’s most exciting and livable cities? We are searching for a strong PhD candidate at the University of Amsterdam (UvA), advised by Dimitrios Tzionas ( and Theo Gevers (, to push together the state of the art! For more details on the project, employment conditions and benefits, and application instructions, see:

Sr. Research Scientist, Vision and Robotics at UII America, Inc. (Cambridge, MA, USA)
UII America, Inc., a subsidiary company of Shanghai United Imaging Intelligence Healthcare Co. Ltd. (UII), is building an organization of highly-motivated, talented and skillful AI experts and software developers to strengthen our R&D power and address the need of our innovative products in the USA market. United Imaging Intelligence (UII) is committed to providing AI solutions for medical devices, imaging, and diagnosis – to helping clients better understand and embrace AI. United Imaging Intelligence is led by two world-renown leaders in the AI industry. Together, they will lead UII in focusing on “empowerment” and “win-win.” UII empowers doctors and equipment in order for doctors and hospitals to win, for research institutions to win, and for third-party companies to win. UII America, Inc. is building a world-class research and development team in Cambridge, MA. We have an immediate opening for Sr. Research Scientist in the field of computer vision and robotics with the following qualification requirements. The candidate should have a PhD Degree in Computer Science, Electrical Engineering, Systems Engineering, or related field; with 5+ years of experience in R&D in 2D/3D Computer Vision or Robotics. Strong knowledge in SOTA algorithms and programming languages (e.g., C++, Python) are required, as well as a proven track record of publications in top-tier conferences and journals in Computer Vision, Machine Learning, Robotics, or related fields (e.g. CVPR, ICCV, ECCV, TPAMI, IJCV, NIPS, ICLR, ICML, IJRR, RSS, etc.). Experience with RGBD sensors, embedded systems and edge-based AI systems is a plus. The goal of the position is to research and develop computer vision and robotics algorithms, i.e., to conduct cutting-edge research and transfer research results into practical product solutions and to lead the changes in future Healthcare with innovations. More information at

Postdoc and PhD Positions at Purdue University
The Department of Computer Science at Purdue University seeks multiple Ph.D. students (starting Spring or Fall 2023) and Postdoctoral Research Associates (flexible start date) with Prof. Aniket Bera. The ideal candidate has a Ph.D. in CS/ECE/EE on a topic related to computer vision, graphics, AR/VR, multi-agent modeling/simulation, robotics, affective computing, or a related AI/ML area. The positions are expected to last one to two years and can start in Fall 2022 (flexible start date). Prof. Bera will be also hiring fully funded MS and Ph.D. positions in Spring/Fall 2023. Ph.D./M.S. Applications admission decisions are taken by the committee, and it’s strongly encouraged that candidates interested should email Prof. Bera their CVs. To apply for a postdoc position, please submit a CV/resume, a research statement, and a list of 3 professional references with their contact information. A cover letter is optional. For inquiries about this position, please email Prof. Bera (

Postdoc openings at Saarbruecken Research Center for Visual Computing, Interaction, and AI – a  strategic partnership between Google and MPI for Informatics
The Max Planck Institute (MPI) for Informatics in Saarbrücken (Germany) and Google have started a strategic partnership to establish the Saarbruuecken Research Center for Visual Computing, Interaction and Artificial Intelligence (VIA) at the MPI for Informatics. The center is looking for postdocs with experience in the research areas of the center, such as: neural rendering and neural scene representations, foundations of machine learning for visual computing, virtual human capture and modeling, human animation, 3D/4D reconstruction and scene understanding, virtual and augmented reality, new interaction paradigms, e.g. for AR, VR, augmented humans. For more information and application instructions, please refer to:

Research Associate Position at RSiM, TU Berlin
We are looking for a Research Associate to conduct research in the field of deep learning based compression of large-scale satellite images. Due to the continuous advances in satellite technology, recent years have witnessed an explosive growth of satellite image archives. To reduce the storage size, satellite images are usually stored in compressed format in the archives. Recently, end-to-end learning based image compression methods have shown outstanding performance when compared to traditional methods such as JPEG2000. However, most of the existing methods are designed for spatial compression and does not consider the spectral redundancy observed in the satellite images. The goals are: 1) to develop learning-based 3D compression methods where not only spatial but also spectral redundancies are compressed; and 2) to explore satellite image analysis in the 3D compressed domain. For details, please click here.

3 year PhD position on “Increasing Robustness of Resource-Constrained Deep Learning Perception” at Bosch Research in Germany
We are looking for a highly motivated prospective PhD student with an excellent Master degree in Computer Science or a related field. The PhD student will work with us on making deep-learning based perception more robust to domain shift and rare corner cases under the additional constraint of limited compute resources for inference. This constraint is relevant when the model needs to run on edge devices for applications such as driver assistance/automated driving, robotics, or video surveillance. PhD candidates in our department will enjoy an inspiring and international environment of researchers in Bosch’s Corporate Research. Networking with other PhD candidates, industry professionals from Bosch, and exchanging with Bosch’s academic partner network are an essential part of doing a PhD at Bosch. For more details on the position and information on the application process, please refer to: . Students interested in the position can also contact Dr. Jan Hendrik Metzen (

3 years Postdoctoral Researcher Position on Physics-based AI at UIT, Norway
The position being announced here relates to Physics-based Artificial Intelligence. The position entails developing machine learning models towards interpretable and scalable artificial intelligence, and with life science interpretations from 2D/3D microscopy (fluorescently-labeled and label-free) image and video data of biological samples as the target application area. The position offers a unique opportunity of developing career in a highly multidisciplinary (artificial intelligence, physics/optics, life science, computational modeling) cutting edge research arena with a potential to create high impact. The candidate will have opportunity to work across two teams – Bio-AI Lab ( and 3Dnanosopy group ( which are both funded through several prestigious EU and Research Council of Norway projects. The normal period of appointment is three years. Start date: early 2023. Interested candidate can contact Dr. Dilip Prasad ( and/or Dr. Himanshu Buckchash (

Postdoc Position – (Neural) Modeling, Capture and Rendering, 3D/4D Reconstruction, Geometric Deep Learning – Max-Planck-Institute for Informatics
The Visual Computing and Artificial Intelligence Department at the Max-Planck-Institute (MPI) for Informatics headed by Christian Theobalt is looking for an outstanding postdoc in the general area of neural modeling and rendering. Example topics of interest are neural modeling and capture, neural and differentiable rendering, 3D/4D reconstruction, deep learning for geometric modeling etc. For more details on the position and information on the application process, please see:

Postdoc Position – Virtual Human Modeling and Animation – Max-Planck-Institute for Informatics
The Visual Computing and Artificial Intelligence Department at the Max-Planck-Institute (MPI) for Informatics headed by Christian Theobalt is looking for an outstanding postdoc in the general area of virtual human modeling and animation. Example topics of interest are: neural and neuro-explicit models for human modeling, reconstruction and animation; reinforcement learning for animation; physics-based animation; text- and audio-driven animation synthesis etc. For more details on the position and information on the application process, please see:

Postdoc “Medical Image Reconstruction, Analysis and Machine Learning” (Harvard Medical School and Massachusetts General Hospital)
We are looking for postdocs to work on “utilizing machine learning-based image reconstruction and analysis to improve the diagnosis and progression tracking of Alzheimer’s disease (AD) and cancer”. The candidates should have proven experience in image analysis, machine learning, computer vision or related fields. For more information, please check the website:

Data Engineer
Reality Defender seeks a data engineer. You’d work on product-oriented dataset for synthetic (deep-fake) media (image, video, audio) detection and tackle cutting-edge deep learning, audio and computer vision data problems with an emphasis on classification and adversarial methods. Apply Here:

Research Engineer (Computer Vision)
Reality Defender seeks computer vision research engineers to join the R&D team. You’d work on product-oriented research for synthetic (deep fake) image and video detection, and tackle cutting-edge deep learning and computer vision problems with an emphasis on classification and adversarial methods. Apply Here:

Research Scientist (PhD) “Computer Vision for Human Action Understanding using Neurosymbolic AI” (A*STAR Singapore)
We are looking for an excellent research scientist (PhD) with a background in Computer Vision and Machine learning to work on human action understanding using neurosymbolic AI approaches. Background in scene graph generation, human object interaction, action recognition, relational learning, inductive logic programming, and causal learning is highly advantageous. Apply here:

Open PhD on Deep Learning in Generative Models in Barcelona
We are seeking a PhD to join the Learning and Machine Perception (LAMP) team in beautiful Barcelona under the supervision of Joost van de Weijer ( The project is on image-to-image and image-to-video generation. For more information check

Postdoc “Biological Image Analysis” (TU Dresden)
Curiosity-driven basic research of fundamental problems in the field of biological image analysis. Call: Further information: 

Postdoc “Theory and application of Deep Neural Networks” (Telecom Paris, Institut Polytechnique de Paris, France)
Position offered within the MultiMedia equipe and focused on computer vision/compression with deep neural networks. PhD on related topics is a mandatory requirement. More details available at

PhD position Data-Efficient Deep Learning for Autonomous Driving
The Intelligent Vehicles Group at TU Delft is looking for highly qualified candidates for a fully funded PhD position in Data Efficient Deep Learning for Autonomous Driving. The candidate will be supervised by Prof. Dr. Dariu Gavrila and Dr. Holger Caesar. For more details see

3 year PhD positions in Deep Learning at University of Modena and Reggio Emilia (Italy)
The AImageLab research group has several open PhD positions on generative models, vision and language integration, explainable AI, continual learning and medical imaging. Proven experience in computer vision, deep learning, or related fields. Excellent oral and written communication skills. Please refer to the website for details:

Research Scientist – AI for Healthcare (A*STAR, Singapore)
IHPC, A*STAR (Singapore) has several Research Scientist (AI for Healthcare) Positions. Candidates should hold a Ph.D. in computer science, data science or other related disciplines. Proven experience in computer vision, deep learning, medical image analysis, or related fields. Excellent oral and written communication skills. Please refer to the website for details:

Open Research Associate Position at TU Berlin
The Remote Sensing Image Analysis (RSiM) Group of TU Berlin seeks to hire a Research Associate to conduct research and development in the field of explainable machine learning for Earth observation. The goals are: 1) the development of robust and interpretable machine learning models by incorporating prior knowledge from the application domain on Earth observation; 2) advancement of methods to interpret and explain the predictions of deep neural networks for various Earth observation applications. For details, please click here.

Postdoctoral Scholar positions with the University of California, San Francisco
Keiser Lab at UCSF combines machine learning and chemical biology methods to investigate how small molecules perturb protein networks to achieve therapeutic effects. We’re looking for highly motivated postdoctoral candidates with a background in machine learning, pathology, biomedical image analysis, or related fields. To learn more about the open postdoctoral positions with Keiser Lab and how to apply click here.

3 year PhD position in deep learning at University of Bonn (Germany)
The Learning and Optimisation for Visual Computing Group at the University of Bonn has an opening for a fully-funded PhD position in the area of “Deep Multi-Modal Image Synthesis for COVID-19 Imaging and Beyond”. Candidates should have a solid theoretical understanding of machine learning techniques and hands-on experience in training deep neural networks. Previous experience with medical image data is not essential but a plus. More details at

2 years postdoc fellow – Computer Vision and Machine Learning/Deep Learning
The Computer Vision Laboratory at Toronto Metropolitan University is looking for a Postdoctoral Fellow in the broad areas of computer vision and machine learning/deep learning. The ideal candidate should have a Ph.D. in a related area with demonstrated ability to conduct high-quality research in computer vision and machine learning and have a track record of publications in top venues. The position is for 2 years with a possibility for renewal. Please refer to the website for details:

2 years postdoc – 3D Transformers for point cloud processing in autonomous driving
A two-year postdoc position is open in the research axis “Vision and 3D Perception for Scene Understanding” of a joint Inria / context, in central Paris (France). We’re looking for good candidates with good records, and motivation to work on 3D point cloud processing. The position *starts on October 1st, 2022*. More details at:

3-year-PhD student Position – working on Image analyses for predicting parturition in cows and pigs
The University of Veterinary Medicine Vienna (Vetmeduni), Clinical Unit for Herd Health Management in collaboration with the Precision Livestock Farming Hub is looking for a PhD student working on “Image analyses for predicting parturition in cows and pigs”. Deadline for applications: 15.05.2022. Please find the detailed job offer in the link: PhD Position Image Analyses. Vetmeduni Vienna works to safeguard the health of animals in Austria through its teaching and research activities and through the services it offers. These tasks represent our contribution to keeping people and their animal companions healthy and to ensuring the production of healthy food.


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