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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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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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. 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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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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(“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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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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the dispersion of these macroplastic items in these flow fields; comparing the results of the simulations to results from an experimental campaign of floating trackers; collaborating with a postdoc and two PhD