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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 7 days ago
learning, or transformers is a major advantage. Practical knowledge of Python, clean coding practices, and reproducible ML workflows. Familiarity with protein structure, biophysics, or molecular modeling (MD
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death. The molecular mechanisms that control how plants respond to, and recover from, acute hypoxia stress are not completely understood. Notably, hypoxia is also an important developmental signal in
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computational modeling of pharmaceutical formulations and molecular recognition processes relevant to drug delivery systems. The work focuses on molecular binding phenomena such as host–guest inclusion complexes
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forming a moist microbial rhizosphere habitat. Your work will build on the process-based soil-rhizosphere-plant model, developed at the Agrosphere Institute, which integrates a 3D functional-structural
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differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical
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and implant models Histology, advanced microscopy, and micro-computed tomography Spatial transcriptomics as well as molecular and bioinformatic analyses The candidate will work in a highly
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mouse models of cancer. The project will use molecular biology, protein biochemistry, and enzyme assays to further characterise this agent and understand its mechanism of action. You will manage your own
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pathways, pain perception, and tissue alterations in chronic joint disease. Using joint tissues as a biologically and clinically relevant model, the project will explore how stress-related signals interact
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trafficking, and copper homeostasis in neuronal systems. This position requires a scientist with advanced technical expertise in the Hoffman laboratory’s core experimental platforms and biological models
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, enzymology, or molecular biology - Experience with computational methods (e.g. de novo protein design, molecular modelling, machine learning, or bioinformatics) - Experience with biochemical or biophysical