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) documented experience in research work on machine learning models with applications in life-science domain; 4) ability to conduct independent research as well as to work effectively in a team, including
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modeling, machine learning, • Experience in human electrophysiological research is a plus, experience in intracranial human research large plus, • Knowledge of cognitive system is a plus, knowledge of
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of the knock-out mouse model. An ideal candidate will have a background in transgenic animals work and cutting-edge histological approaches (incl. RNAscope, tissue clearing and expansion microscopy apart from
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Infrastructure? No Offer Description We offer: ● a unique opportunity to participate in a research project that utilises state-of-the-art data and methods (i.e. online tracking data and deep machine learning
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metabolites associated with treatment efficacy, as well as the development of machine learning models with high predictive performance and strong biological interpretability. The ultimate aim of the project is
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, with particular emphasis on modeling, rigging, and animation, 5) Academic achievements – artistic or design achievements related to computer graphics, animation, or digital media, 6) Organizational
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | about 2 months ago
3 Aug 2026 Job Information Organisation/Company The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences Research Field Biological sciences » Biology Researcher
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studies for the following degree programmes: Physics and/or Applied Computer Studies and/or Computer Studies or related degree programmes, ability to teach classes using the tools for distance learning
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, and treatment with patient‑derived anti‑IgLON5 antibodies and other experimental modulators to model disease‑relevant tau pathology. Single‑cell characterization of immune responses and cellular
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, permeability, and cytochrome P450 interactions would be advantageous; ▪ Knowledge and/or openness to learn of computer-aided drug design methods, in particular molecular docking, pharmacophore modelling, or in