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Engineering, Medical Image Analysis, Applied Mathematics or a related field Experience with deep learning for image analysis, preferably in medical imaging Experience with generative modelling, ideally
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the measurement instrument in close collaboration with our industrial partner, Veridis Technologies. An ideal candidate has experience in vibrational spectroscopy and spectral processing. Expertise in deep learning
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scientific curiosity. You thrive at the boundary of robot learning, computer vision, deep learning, and simulation, and you are excited to see your research running on real robots. You communicate clearly
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for this position, the following is required: PhD in data or computer science, machine learning, AI, statistics, mathematics, biophysics, bioinformatics. Additional requirements In addition to your CV and your
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. You have: A PhD in Computer Science, Machine Learning, Applied Mathematics, Scientific Computing, Data Engineering, or a closely related field. Demonstrated ability to conduct high-quality academic
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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
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feed into this vision. The intended start date is July–August 2026. Job requirements PhD in machine learning, artificial intelligence, computational chemistry, computational materials science, or a
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of receiving their PhD. In particular for this position, the following is required: PhD in data science, AI, computer science, machine learning, Earth system science, climate etc., with a thesis subject relevant
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from the areas of few-shot learning, continual learning and modular deep learning, as well as different LLM alignment frameworks, based on reinforcement learning and direct preference optimisation
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a key contributor in growing their P&L from $75 million in 2005 to $1.15 billion in 2008 . Previously Ben earned a PhD in Math (Algebraic Topology under Peter May) from the University of Chicago