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macromolecular dynamics with statistical mechanics, molecular simulation at different resolutions, machine learning, and experimental data. Our group works on the definition and implementation of strategies
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(bioinformatics, computer science, genetics, or a related field) Excellent advanced scientific degree (PhD) in bioinformatics, computer science, computational biology or a related STEM field; prior working
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extension, in the programme area "Next-Generation Horticultural Systems" (HORTSYS), in the research group "Open Field Horticultural Systems" within the EU-HORIZON project NitroScope - "Scoping European N
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on the Part Scale. The project is jointly supervised by Prof. Dr. Ralf Jänicke (Institute of Applied Mechanics, Technische Universität Braunschweig) and PD Dr. Stefan Kollmannsberger (Chair of Computational
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | 7 days ago
Access to state-of-the-art scientific infrastructure and training (including imaging, scientific computing and data visualization, proteomics, and electronics facilities, and a mechanical workshop
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organismal systems across diverse biological contexts. Using a blend of cutting-edge experimental and computational approaches, we strive to decode and model complex biological processes—from single-cell
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of genotype-phenotype interactions, to promote understanding of the genetic mechanisms affecting past and present observable traits. The position should start on January 1st, 2026 and will be limited to five
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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/d) in Energy Informatics. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant and international research
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transfer. Its current five-year scientific programme, Molecules to Ecosystems (2022–2026), aims to deepen our understanding of life — from molecular mechanisms to complex ecosystems — with a strong emphasis