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, TensorFlow), is essential for developing and adapting advanced AI models to integrate heterogeneous datasets. You exhibit solid analytical skills, the ability to design robust computational workflows
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focus is the interplay of these factors with mitochondrial translation systems and respiratory chain complex assembly. We use the yeast Saccharomyces cerevisiae as our primary research model. In
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into elementary particle physics from model building and Dark Matter to formal Quantum Field Theory. Organizationally we are part of the division of Subatomic, High-Energy and Plasma Physics within the Department
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patterns of genomic sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models
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ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real
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develop and improve protein-glycan binding prediction models and use AI, data science, and bioinformatics to identify and design glycan-binding proteins with desired binding specificities. Qualifications
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. The workplace The position is located at the Laboratory of Organic Electronics (LOE ), specifically within the Theory and Modelling for Organic Electronics unit in the group led by Associate Professor Glib
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techniques • Explainable AI/ML using visualization • AI/ML-empowered visual analytics of multivariate networks (network embeddings, …) • Large Language Model (LLM)-assisted visual analytics of text, images
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will be expected to dedicate your time develop a high-biofidelity, high-resolution computational rat model with dual applications: i) advance the mechanistic understanding of brain injury by linking
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approach combines behavioral experiments, psychophysiology, computational modeling, and brain imaging (fMRI). We offer a dynamic, international research environment where you can contribute to top-level