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17 Apr 2026 Job Information Organisation/Company Luxembourg Institute of Science and Technology Research Field Computer science Researcher Profile Recognised Researcher (R2) Positions Postdoc
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neurological disorders, novel applications of deep brain stimulation technology to the treatment of neurological and psychiatric disease, the mechanisms of deep brain stimulation and finally motor and reward
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, public, urban research university located in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment to excellence
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will be to use machine learning approaches (deep neural network architectures) to design representations and transferable energy models for proteins. Various resolutions will be investigated in
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symbiosis of cutting-edge AI combined with human support. About the role The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner
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include the development of finite elements methods, as well as inverse design strategies based on deep-learning and Neural Networks approaches. The latter will then bring the project to the experimental
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
applicant will contribute to the AIGLE project by: · Developing innovative scientific Deep Learning/Machine Learning algorithms for flash flood forecasting. · Contributing to the collection
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to advance the project. The successful candidate will have extensive experience developing models and algorithms for analysis of noisy biological data, a deep background in analysis of stochastic processes
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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | about 1 month ago
, Approximation Theory, Machine Learning, Inverse Problems and Regularization Theory. Proficiency in programming with a strong preference for Python and deep learning frameworks such as PyTorch is highly desirable
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deep experience with PyTorch, JAX, or TensorFlow. Broad knowledge of modern ML and optimization (gradient‑based, evolutionary, Bayesian, reinforcement learning). Hands‑on experience with generative