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Details A brain decoding model aims at predicting what sensory stimulus is received (e.g. visual stimuli, different images), which mental state is experienced (i.e. asleep, awake, drowsy) or even what is
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. We use advanced computational technologies to discover how biomolecules and organisms function and interact. We pioneer new methods for prediction, prevention, diagnostics and treatment of diseases
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bioinformatics for immunology research programs. You'll work at the cutting edge of AI-enhanced immunology, applying deep learning, foundation models, and advanced machine learning approaches to understand how
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background in nonlinear optics, ultrafast photonics, and integrated photonics, alongside the ability to develop predictive models for optical materials and photonic devices. The successful candidate will work
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to identify metabolic response patterns and develop predictive models for personalized nutrition. Supervising master’s and/or doctoral students to a certain extent Possibility to engage in teaching at
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: Implementation and fine-tuning of antibody design models (RFdiffusion and boltzgen, AlphaFold3 etc.). Implementation of affinity prediction and maturation (FoldX, RosettaFold, ESM etc.), virtual screening and
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to predict thermal runaway on the cell level. The combustion and gas model developed on the cell level will then feed into the work to accurately predict thermal runaway on pack, module, and system levels
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, prior distributions and posterior predictive checks, model comparison, programming in R (python/Matlab), implementations using R-packages rstan/JAGS and brms/STAN or equivalent interfaces. References
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Actionable Data for Opioid Response in KY (RADOR-KY) project. This position will build data science solutions and predictive models for time series forecasting systems related to risk prediction, outcome
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large datasets in wheat, Develop and implement novel approaches for genome-wide predictions of complex traits. Your qualifications and skills: You hold a MSc in plant science, plant breeding, biology, or