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Helmholtz-Zentrum für Infektionsforschung GmbH | Braunschweig, Niedersachsen | Germany | about 2 months ago
127_2025_VIRI_PhD_final.pdf English (152.27 KB - PDF) Download Additional Information Benefits Modern laboratories, incl. BSL3Bi State-of-the-art analytical instrumentation (spectral analyzer, sorting facility, single cell
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theses Your Profile: You have successfully completed your studies in economics, (business) engineering, natural sciences, or data science with very good results Knowledge in the fields of environmental
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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design
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analytical chemistry, mass spectrometry, or trace gas measurements is an asset Enthusiasm for laboratory and field work Willingness to engage in programming and data analysis (preferably Python) Excellent
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science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in Python Independent and analytical way of working Reliable and thorough
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infections We offer: Modern laboratories, incl. BSL3Bi State-of-the-art analytical instrumentation (spectral analyzer, sorting facility, single cell genomics pipelines) Ample biological profiling platforms (in
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2 Oct 2025 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile First Stage Researcher (R1) Country Germany Application Deadline 19 Jan 2038 - 03:14
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3 Oct 2025 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile First Stage Researcher (R1) Country Germany Application Deadline 19 Jan 2038 - 03:14
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presentation and publication of the results Requirements: university degree (Master's or equivalent) in geodesy or a related subject (geophysics, geoinformatics, physics, mathematics) excellent analytical skills
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements