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Your Job: Reinforcement Learning (RL) is a versatile and powerful tool for control, but often data-inefficient, requiring numerous updates and non-local information such as replay buffers and batch
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degree (or equivalent) in Data Science, Computational Biology, Bioinformatics, Computer Science, Physics or a related field Solid programming skills and knowledge in deep learning, statistical modelling
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with the opportunity to complete a high-quality dissertation participation in a dynamic research team with supportive colleagues, fostering collaboration and mutual learning l a lively community of PhD
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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, particularly deep learning and optimization methods Excellent coding skills, particularly in Python and machine learning frameworks (PyTorch or Jax) The ability for creative and analytical thinking across
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Description We offer a deep immersion in bio-based energy technologies; the candidate will learn and live the translational perspective of designing biomaterials for sustainable energy-related applications
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Cancer Consortium (DKTK). For the DKTK partner site Munich, we are seeking for the next possible date a PhD Student in Mutational Processes Driving Somatic Evolution Reference number: 2025-0224 From
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in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning, particularly deep learning and optimization methods Excellent
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of the PhD topic (subproject A7- Reinforcement learning for mode choice decisions): This PhD project will develop and implement a Deep Reinforcement Learning (DRL) model for dynamic mode choice within
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image