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Recent breakthroughs in Artificial Intelligence resulted in the emergence of the first generation of foundation models that are capable of transfer across conditions and tasks. This opened entirely new ways to solve domain-specific problems by training transferable models and adapting those in a data- and compute-efficient manner to various problem settings. However, the perceptual possibilities are critically hindered by the language-focussed optimization of current foundation models, fundamentally limiting their ability for spatial reasoning, temporal logic, and operating in low-resource scenarios, which leads to shortcut learning and hallucination at test-time. This PhD project focuses on a new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms.
Recent breakthroughs in Artificial Intelligence resulted in the emergence of the first generation of foundation models that are capable of transfer across conditions and tasks. This opened entirely new ways to solve domain-specific problems by training transferable models and adapting those in a data- and compute-efficient manner to various problem settings. However, the perceptual possibilities are critically hindered by the language-focussed optimization of current foundation models, fundamentally limiting their ability for spatial reasoning, temporal logic, and operating in low-resource scenarios, which leads to shortcut learning and hallucination at test-time. This PhD project focuses on a new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms.
You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to invent, develop and evaluate novel methods for pre-training and fine-tuning of perceptual foundation models, that expand their sensing abilities, generalize at deployment, and do so in an efficient and sustainable way. Importantly, the models should transfer to specialist industrial use cases. The research is embedded in the Video & Image Sense lab at the University of Amsterdam, and you will actively collaborate with our partner TNO within the NWO Perspectief Foundation for Industry (FIND) project. The overall FIND project brings together 5 universities with 10 labs, 11 Dutch companies, ranging from start-ups to multinationals, and 2 knowledge institutes to pave the way for a new wave of AI-based automation that helps the Dutch industry strengthen and keep its international competitive advantage as a leading high-tech nation in the AI-era. FIND uniquely focusses on data types that are underserved by current foundation models and specifically addresses industry-relevant, low-resource, privacy-sensitive edge applications.
Tasks and responsibilities:
A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is December 1st 2025. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.
The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 3,059 to € 3,881 (scale P). This does not include 8% holiday allowance and 8,3% year-end allowance. The UFO profile Promovendus is applicable.. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.
Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:
Are you curious to read more about our extensive package of secondary employment benefits, take a look here.
You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to invent, develop and evaluate novel methods for pre-training and fine-tuning of perceptual foundation models, that expand their sensing abilities, generalize at deployment, and do so in an efficient and sustainable way. Importantly, the models should transfer to specialist industrial use cases. The research is embedded in the Video & Image Sense lab at the University of Amsterdam, and you will actively collaborate with our partner TNO within the NWO Perspectief Foundation for Industry (FIND) project. The overall FIND project brings together 5 universities with 10 labs, 11 Dutch companies, ranging from start-ups to multinationals, and 2 knowledge institutes to pave the way for a new wave of AI-based automation that helps the Dutch industry strengthen and keep its international competitive advantage as a leading high-tech nation in the AI-era. FIND uniquely focusses on data types that are underserved by current foundation models and specifically addresses industry-relevant, low-resource, privacy-sensitive edge applications.
Tasks and responsibilities:
A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is December 1st 2025. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.
The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 3,059 to € 3,881 (scale P). This does not include 8% holiday allowance and 8,3% year-end allowance. The UFO profile Promovendus is applicable.. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.
Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:
Are you curious to read more about our extensive package of secondary employment benefits, take a look here.
The Faculty of Science has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.
The mission of the Informatics Institute (IvI) is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.
The position is with Prof. dr. Cees Snoek, Professor, head of the Video & Image Sense lab (VIS lab), at the University of Amsterdam. VIS lab is a world-leading lab on Computer Vision and Machine Learning, and has over 30 PhD students, postdoctoral researchers and faculty members working on a broad variety of deep learning, computer vision, and foundation model subjects, like self-supervised learning, diffusion models, and test-time generalization for perception tasks like object detection, instance segmentation and activity recognition. The position is also embedded in the European ELLIS Network of Excellence in AI. We also anticipate regular visits to project partner TNO in the Hague.
The Faculty of Science has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.
The mission of the Informatics Institute (IvI) is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.
The position is with Prof. dr. Cees Snoek, Professor, head of the Video & Image Sense lab (VIS lab), at the University of Amsterdam. VIS lab is a world-leading lab on Computer Vision and Machine Learning, and has over 30 PhD students, postdoctoral researchers and faculty members working on a broad variety of deep learning, computer vision, and foundation model subjects, like self-supervised learning, diffusion models, and test-time generalization for perception tasks like object detection, instance segmentation and activity recognition. The position is also embedded in the European ELLIS Network of Excellence in AI. We also anticipate regular visits to project partner TNO in the Hague.
If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the apply button. We accept applications until and including 10 October 2025. Applications should include the following information (all files besides your CV should be submitted in one single pdf file):
A knowledge security check can be part of the selection procedure (for details: national knowledge security guidelines).
Please use the CV field to upload your resume as a separate pdf document. Use the Cover Letter field to upload the other requested documents, including the motivation letter, as one single pdf file. Only complete applications received within the response period via the link below will be considered.
Do you have any questions or do you require additional information? Please contact:
If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the apply button. We accept applications until and including 10 October 2025. Applications should include the following information (all files besides your CV should be submitted in one single pdf file):
A knowledge security check can be part of the selection procedure (for details: national knowledge security guidelines).
Please use the CV field to upload your resume as a separate pdf document. Use the Cover Letter field to upload the other requested documents, including the motivation letter, as one single pdf file. Only complete applications received within the response period via the link below will be considered.
Do you have any questions or do you require additional information? Please contact: