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Field
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, including parallel computing frameworks, C/C++, Julia and/or python Experience with training AI surrogate and/or inverse models Experience working in underground laboratories and/or clean rooms Excellent
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photoautotrophic and aerobic heterotrophic growth to enhance lipid and pigment productivity. In parallel, customised downstream processing strategies are developed for the extraction and purification of lipids
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link to the application form, please visit the Fulbright website . The call for academic year 2025/26 is closed, keep an eye on the Fulbright website for a new call in Autumn. Parallel with
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of human biological fluids (such as blood and urine), to ensure successful implementation in various clinical and exposomics applications. In parallel, methods for targeted metabolomics/lipidomics need to be
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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, or network-based modeling of infrastructure or industrial systems. Familiarity with high-performance computing, cloud computing, or parallel computing environments for training models and solving optimization
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scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation Experience applying machine learning or AI to molecular simulation
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freely behaving rodent pups. A parallel research line investigates the circuit-level basis of spatial memory in the entorhinal–hippocampal system in adult animals. The group uses in vivo multi-site
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introduced by our group while developing new ones, and we couple this work with innovative strategies to define the molecular basis for their modes of action in bacterial cells. In parallel, we investigate how
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associated with biological membranes, including large peripheral membrane complexes and integral membrane transporters. In parallel with mechanistic structural work, we develop targeted chemical probes