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    • Amsterdam
  • Full time
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  • Computer science
  • Mathematics
  • Physics


  • Postdoc
  • Researcher

Apply by: 2022-09-30

Postdoctoral Researcher on Deep Learning and Dynamical Systems, PDEs, for Science (2 years)

Published 2022-07-05

Are you passionate about bleeding edge research on Deep Learning and Dynamical Systems, (Stochastic) Partial Differential Equations, for Sciences? Can we discover, model and explain dynamics inside Neural Networks? Can we use Neural Networks to solve better, more efficiently, more generally, Ordinary and Partial Differential Equations, or stochastic versions of them?

We are looking for a postdoctoral researcher with either Machine Learning, Physics, Applied Mathematics, or Computer Vision background to join a team of 20 researchers working on these very topics (2 years contract); a team that is connected with the ELLIS Network of Excellence in AI; a team with consistent and strong presence in the top Machine Learning and Computer Vision conferences and journals.

What are you going to do
Beyond static data, static learning, static algorithms, the next innovation in Machine and Deep Learning will be in the direction of Neural Networks Dynamics, Dynamical Systems, and PDEs with focus on scientific data. We are looking for a Postdoctoral researcher who is just as passionate to invest in this direction.

Understanding space and time in machine learning, be it with neural networks, Markov models, deep probabilistic models, and beyond, is one of the biggest problems, especially given the vast availability of video and other high-dimensional time series data. While consumer videos are unconstrained and thus unclear how or what to model about them, 'videos' of spatiotemporal scientific recording offer a great opportunity for innovation. For one, they pertain certain and complex spatiotemporal dynamics that modern machine learning algorithms cannot easily model beyond restricted cases. What is more, the underlying science of these dynamics can be used to evaluate and compare algorithms rather than relying on biased human annotations for that. Third, scientific data are almost always spatiotemporal, they are vast and grow at an immense rate, and are ready to be understood by algorithms.

Given all the evidence and potential impact, part of this position will also be co-designing and creating a Spatiotemporal Dynamical Systems Decathlon, which would hopefully act as a catalyst for future research in this direction. This is an ongoing initiative already started and led by the PI, E. Gavves. In this Decathlon we will be organizing scientific data from different disciplines together with respective leading experts, and designing experiments that showcase the value of learning to simulate physical processes across fields.

Learning to simulate is and will keep being an exciting and entirely novel direction of machine learning research both in academia and industry. The PostDoctoral researcher will have the opportunity to work with a team of 20 Ph.D. students working on these problems. The funding is from personal grants with little strings attached, and fundamental research is possible and desirable.

Tasks and responsibilities:
  • show independence in achieving research goals and willingness to collaborate and to supervise PhD students working on deep learning and dynamical systems, differential geometry, sciences;
  • co-lead a large initiative of researchers from multiple disciplines (physics, fluid dynamics, astronomy, biology, chemistry) on developing the Spatiotemporal Dynamical Systems Decathlon;
  • invent, evaluate, and describe novel learning algorithms for spatiotemporal PDE and dynamical systems;
  • contribute to a real-world showcase demo;
  • present research results at international conferences, workshops, and journals;
  • become an active member of the research community and to collaborate with other researchers, both within and outside the Informatics Institute;
  • contribute to teaching activities, such as lectures, lab courses, or supervising bachelor and master students.
Your experience and profile:
  • A PhD in either an AI-related field (Machine Learning, Computer Vision, Deep Learning) or a Natural Science field ((Applied) Mathematics, Physics, Fluid dynamics, Astronomy, etc);
  • the ability to invent and evaluate novel algorithm, and present these orally and in writing;
  • committed researcher, demonstrated by publications in the top machine learning, computer vision, or other top scientific conferences and journals;
  • enthusiastic about Machine Learning and Science and how to interface them
  • the ability to implement and evaluate machine learning algorithms in Python with deep learning toolkits (PyTorch, TensorFlow);
  • the ability to implement and evaluate simulations with partial/stochastic differential equation solvers using state-of-the-art libraries;
  • the ability to work well in teams and communicate fluently in written and spoken English.
We offer a temporary employment contract for 38 hours per week for a period of 24 months. The preferred starting date is as soon as possible.

The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 2,960 to € 4,670 (scale 10). This does not include 8% holiday allowance and 8,3% year-end allowance. The UFO profile Researcher 4 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:
  • 232 holiday hours per year (based on fulltime) and extra holidays between Christmas and 1 January.
  • Multiple courses to follow from our Teaching and Learning Centre.
  • A complete educational program for PhD students.
  • Multiple courses on topics such as leadership for academic staff.
  • Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses.
  • 7 weeks birth leave (partner leave) with 100% salary.
  • Partly paid parental leave.
  • The possibility to set up a workplace at home;
  • A pension at ABP for which UvA pays two third part of the contribution.
  • The possibility to follow courses to learn Dutch;
  • Help with housing for a studio or small apartment when you're moving from abroad.
Are you curious to read more about our extensive package of secondary employment benefits, take a look here.

Faculty of Science
The University of Amsterdam is the Netherlands' largest university, offering the widest range of academic programmes. At the UvA, 30,000 students, 6,000 staff members and 3,000 PhD candidates study and work in a diverse range of fields, connected by a culture of curiosity.

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 Video & Image Sense lab (VIS) studies computer vision, deep learning and cognitive science, making sense of video and images with artificial and human intelligence. It positions itself within the AI research theme, with clear links to the Data Science theme of the Informatics Institute.

The VIS Lab is strongly embedded in the larger UvA and Amsterdam artificial intelligence ecosystem with connections to multiple public-private Innovation Centres for AI (ICAI) labs and spin-off's including Kepler Vision Technologies and Ellogon.ai.

The position is with Dr. Efstratios Gavves, Associate Professor in the Informatics Institute at the University of Amsterdam. Dr Gavves and ERC Starting Grant laureate, who is more than happy to help with mentoring on how to develop an excellent academic profile, including how to work on a vision, prepare proposals, and of course collaborate in excellent research. At the University of Amsterdam, we have an open and friendly attitude to open research, collaborations, and independent thinking.

Want to know more about our organisation? Read more about working at the University of Amsterdam.

Do you have any questions or do you require additional information? Please contact:
  • Efstratios Gavves, Associate Professor on Computer Vision and Deep Learning.
  • T: +31 (0)681495511