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, immunology, and biotechnology. The project integrates expertise in liver biology, disease modelling, quantitative omics, and advanced experimental platforms, including automated organoid culture systems, AI
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We are seeking highly motivated and talented applicants for a 1-year postdoctoral position (with the possibility of 1-2 year extension) in the area of efficient foundation model inference. Join us
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of Parkinson’s Disease. As part of the consortium, you will apply stem cell models to investigate how pesticides and toxicants exert toxicity on human neurons, and you will interact closely with toxicologists
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complement the Department’s ongoing activities in landscape-scale modelling, with a specific focus on nature-based solutions in agricultural landscapes. The successful candidate will be integrated
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application of cumulative impact assessment model using food webs, which is intended to assess impact of multi-stressors on trophic and non-trophic interactions networks. The modelling will be primarily based
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modelling methods to design resistance-proof antibiotics. You will join an interdisciplinary team, integrating machine learning, medicinal chemistry and microbiology. You will work with Asst. Prof. Eli N
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at the single-atom level Understanding of atomic mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. 4. Modeling Atomic Processes on Nanoparticles You
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Two postdoctoral positions (3-year) in Experimental Evolution of Methanogenic Microbiomes in Bioe...
) This position centers on directed laboratory evolution of defined microbial communities under controlled bioelectrochemical conditions. You will run evolution experiments with constructed consortia, track
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or similar. Experience in handling dynamic modelling and control, experimental setup and testing, Digital Twin and Machine Learning Publication experience Collaboration and/or management skills Communication
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includes the following tasks: Develop computer-aided design software for modular construction of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models