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is focused on the development of high-fidelity reacting flow models to investigate thermal runaway in battery cells, pack, modules, and systems. Generally speaking, thermal runaway is a chain reaction
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breakthroughs in deep learning–powered protein design, recognized by the 2024 Nobel Prize in Chemistry, have enabled the creation of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and
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process involve developing models for the components of both axial and radial turbomachines. A strong background in aerodynamic methods and tools of turbomachinery design is therefore required, which in
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Experience in energy system modelling Teaching experience Consideration will also be given to how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how
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be made for special reasons). Experience in research on digital cultures. Proficiency in AI methods (e.g., NLP techniques, machine learning, and large language models, LLMs)—including web scraping
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(attoswitch.eu). Detailed description of the work duties, such as: Device design and layout. DC- and 1/f noise characterization of devices. Data analysis and interpretation. Device modelling in collaboration with
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fluid mechanic modelling of particle trajectories in acoustically actuated microfluidic systems. Experience of acoustic enrichment/trapping of nanoparticles or extracellular vesicles Experience in
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. Eran Elhaik to design machine-learning models that unlock the potential of genomics for forensic investigations and historical reconstructions. Work duties We aim to develop machine learning methods