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techniques, such as neural motion models and physics-based simulation, enable the creation of lifelike animations with reduced manual intervention, benefiting industries like gaming, film, and virtual
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primarily to Task 5 of the project, focused on functional validation in cancer cell models. The researcher will define and implement relevant cellular models in collaboration with the partner institution i3S
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professional role model. Coach and nurture students. Clean building floors. Follow procedures for the use of chemical cleaners and power equipment. Mix chemicals according to specifications. Notify managers
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 9 days ago
of Computational Biology (ICB) , as part of the Computational Health Center at Helmholtz Munich, is globally recognised for innovations in data analysis and modelling of biological systems and diseases, anchored
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threats, using in vitro exposure-response assays, RNA and whole-genome sequencing, PK/PD modeling, and high-resolution microscopy. This interdisciplinary approach challenges current resistance paradigms
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Postdoctoral researcher in theoretical modeling of supernovae Through this opening we are looking for a motivated researcher to join the stellar astrophysics group of Prof. Pablo Marchant, within the context
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models. Building on our preliminary work using retrograde tracing and live-cell imaging to map GB-neuron connectivity, we aim to identify molecular targets for therapeutic intervention. Job description As
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Education) is a statewide model demonstration project housed at the University of Idaho designed to promote competitive integrated employment (CIE) within post-secondary education (IPSE) programs for students
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biophysical network models of The Virtual Brain (TVB) type, we aim to mechanistically explain patient heterogeneity and identify prognostic biomarkers. This is a high-impact, interdisciplinary project bridging
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neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning rules in networks of complex spiking neuron models in the application field of geolocalization: Building