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Join us to pioneer next-generation generative models that accelerate molecular dynamics. We seek a postdoctoral researcher to develop AI surrogates for molecular dynamics (MD), slashing
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spinal cord as a model system. You will engage a systematic strategy to identify these mechanisms by generating innovative mouse genetic strains, identifying embryonic defects and the underlying molecular
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CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with an ability to interpret and analyze simulation and/or experimental results. Ability to work in
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contributions in: Building novel generative models for predicting genome-scale evolutionary patterns using GenSLMs Developing scalable models that can, when integrated with high throughput molecular dynamics
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., multivariate statistics, linear and generalized linear mixed effects models, PCAs, PCoAs, RDAs, and permutational approaches) of large integrated datasets including ecological, environmental, molecular, and
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molecular dynamics, enhanced sampling, and kinetic modeling—the team investigates how neurotransmitters like norepinephrine and hormones such as estrogen interact with β-adrenergic and estrogen-related GPCRs
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comprehensive simulation open-source codes. Experience in data analysis and simulations of complex and coupled nuclear engineering problems, using techniques such as (but not limited to) molecular dynamics
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processing 2. nonequilibrium physics of molecular machines 3. understanding the role of phase-separated condensates with quantitative models 4. Modeling multicellular systems in mechanobiology 5. AI assisted
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collaboration with the national (GTK, CSC) and international project partners (Karlsruhe Institute of Technology). Perform ab initio molecular dynamics (MD) simulations together with consortium partners
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related field are particularly encouraged to apply.We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular