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Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) | Leipzig, Sachsen | Germany | 3 months ago
research on population coding and Alzheimer’s disease Key research methods: fMRI (including 7T), MEG, virtual reality (VR), a wide variety of cognitive tasks, psychophysics, machine learning, deep neural
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concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical
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. You are expected to bring deep mechanistic insight, drive the scientific narrative, and leverage our robust pre-clinical modelsâ”complemented by our clinical trial multi-omic dataâ”to build your own
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
-10346 Requirements Skills/Qualifications PhD in Computer Science, Machine Learning, Signal Processing, or a closely related field, completed or nearly completed at the start date. Strong background in
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/deep learning-based medical image analysis methods for computerised tomography scans (CT scans). Key applications of such ML/DL methods are illustrated by our prior research (PMIDs 33913675, 33234786
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At AAU Energy, a position as Postdoc in AI and Deep Learning for Radar-Based Non-Destructive Testing is open for appointment from 01.10.2026 or as soon as possible hereafter. The position is
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. This large multimodal dataset allows us to estimate and test different computational models of the decision and learning processes. One postdoc is currently working on the MEG and iEEG data, and one PhD
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about applying deep learning to decode the regulatory grammar of plant genomes and translating predictions into testable biological hypotheses, we invite you to join the Omics Data Analysis and
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. Experience with deep learning and programming, preferably in Python, are required and should be evident from your academic track record, including the (online) courses you've followed, your publications