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We are seeking an exceptional and highly motivated Postdoctoral Researcher to lead research on the in-hospital deployment of Large Language Models (LLMs). The focus of this position is the
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for reaction-diffusion systems Enhancing the biophysical capabilities of the C++ framework Applying the framework to morphogenetic questions using real imaging data Running large-scale simulations on ETH’s HPC
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explore possibilities to enhance the sensitivity of Magnetic Resonance (ESR and NMR) by harnessing the large spin polarization of photo-excited triplet states in a broadly applicable manner. Curious? So are
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therapeutic targets. These efforts produce large-scale, rich in vivo perturbation datasets. The computational challenges include building scalable and reproducible pipelines for guide demultiplexing and
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can we use Foundation Models, VLMs, VLAs, and robot learning for complex and long-horizon tasks that involve manipulation, locomotion, and navigation in potentially unstructured and large-scale
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formulating constitutive and damage laws that capture cavitation-driven processes, implementing and verifying robust large deformation solvers, and performing rigorous verification and validation using datasets
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micrometeorology, greenhouse gas exchange, tree and/or ecosystem physiology Relevant research experience can be based on observations, modelling or statistical analyses Excellent command of large data analyses as
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-cell data) using existing pipelines Demonstrated ability to enhance, optimize, and extend existing computational pipelines, as well as design and implement new workflows Experience working with large and
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, ample lab space and technical support, and a rich scientific environment with a large and active community. This position is available upon agreement and is in the lab of Prof I. Mansuy, Laboratory
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collection. This position aims to synthesise all available information from these natural fungal isolates to build hypotheses for which genetic features are essential for horizontal transfer. Job description