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interdisciplinary program, HEIBRiDS trains young scientists in Data Science applications within a broad range of natural science domains, spanning from Earth & Environment, Astronomy, Space & Planetary Research
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natural sciences expertise in materials science and materials engineering, in particular methods of computational material science (e.g. DFT, CALPHAD) programming skills, e.g. Python basic knowledge of data
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sequencing, RNA sequencing, mouse models, iPSC-derived organoids, and functional genomics approaches. The lab has strong collaboration partner in computational biology and bioinformatics, and the candidate
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The Planetary Sciences and Remote Sensing research group at the Institute of Geological Sciences at the FU Berlin participates in various experiments in space missions of ESA, NASA and JAXA. In our
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Master's student in physics, mechanical engineering, materials science or a comparable degree programme and have a connection to software development. You are characterised by an independent and
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-regulatory network changes. The project is part of the HEROES-AYA consortium of the German Decade against Cancer, a collaboration between multiple sites in Germany, and the Computational Biology lab of Anna
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systems for measurement processes, or innovative hardware and software for quantum computers and quantum sensors: we develop tomorrow's technology in-house for a sustainable and secure society. When will
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part of Helmholtz networks, e.g., HIRSE; https://www.helmholtz-hirse.de and internationally Your Profile: University degree (Master, Diploma) in natural sciences, computer science or engineering PhD in
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spiking neural networks Your Profile: Current master studies in physics, computer science, mathematics, electrical/electronic engineering or a related science or engineering field Strong background in
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experimental planning, bioinformatic consulting, and in-depth data interpretation, where applicable Your qualifications Master’s degree or PhD in Bioinformatics, Computer Science, Applied Statistics, or a