Machine-learning-nederland March 2024

machine-learning-nederland@list.uva.nl

3 participants
3 discussions

PhD position in epistemology of machine learning (3y), MCMP, LMU Munich
by Tom Sterkenburg 28 Mar '24

28 Mar '24

The Emmy Noether junior research group "From Bias to Knowledge: The Epistemology of Machine Learning," led by Dr. Tom Sterkenburg, investigates the philosophical foundations of machine learning. The group's main aim is to improve our understanding of inductive bias, by building bridges between the philosophy of science and the mathematical theory of machine learning. The group is embedded within the Munich Center for Mathematical Philosophy (MCMP) at LMU Munich. We are looking for a PhD candidate with an excellent master's degree in philosophy, logic, computer science, or related areas. You have a background and strong interest in the philosophy of artificial intelligence and/or philosophy of science, and ideally affinity with the mathematics and epistemology of machine learning. Deadline for applications: 1 May 2024. Intended starting date: 1 October 2024. For further information, please see https://job-portal.lmu.de/jobposting/fc186685c55c8407077908d81755f8881e4265….

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Associate Professor Position in Fundamental Machine Learning at TU Delft
by Jesse Krijthe 22 Mar '24

22 Mar '24

Associate Professor Position in Fundamental Machine Learning at TU Delft We are looking for an enthusiastic new colleague to come work with us on fundamental topics in machine learning. For more information and details on the application procedure, please see: https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?… Application deadline: 15 April 2024

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CWI seminar Nils Thuerey
by Wouter Edeling 19 Mar '24

19 Mar '24

Dear all, The next speaker in our Seminar for machine learning and UQ in scientific computing will be Nils Thuerey, associate-professor at the TU Munich. He will talk about creating probabilistic surrogates using diffusion models and differentiable solvers, see the abstract below. The talk will take place at 11AM CET. For those at CWI, the location will be L017 and a Zoom link is attached for online attendees. Kind regards, Wouter Edeling Join Zoom Meeting https://cwi-nl.zoom.us/j/84894449753?pwd=Z3VYY2sxVEJDdDJMdUhmcGwyUXdzUT09 Meeting ID: 848 9444 9753 Passcode: 631919 28 March 2024 11h00 CET, Nils Thuerey, Probabilistic Fluid Simulations: Diffusion Models & Differentiable Solvers This talk focuses on the possibilities that arise from recent advances in the area of deep learning for physics simulations. In particular, it will focus on diffusion modeling and numerical solvers which are differentiable. These solvers provide crucial information for deep learning tasks in the form of gradients, which are especially important for time-dependent processes. Also, existing numerical methods for efficient solvers can be leveraged within learning tasks. This paves the way for hybrid solvers in which traditional methods work alongside pre-trained neural network components. In this context, diffusion models and score matching will be discussed as powerful building blocks for training probabilistic surrogates. The capabilities of the resulting methods will be illustrated with examples such as wake flows and turbulent flow cases.

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Machine-learning-nederland March 2024