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on model surfaces In situ and operando (surface) X-ray scattering studies of catalyst/polymer interfaces Design, optimization, and testing/benchmarking of reactors for in situ and operando studies
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-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications
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Your Job: Help us shape the energy transition! As part of your doctoral studies, you will support the development of innovative stack designs, operating strategies and measurement methods for power
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University Medicine Dresden PhD Position (m/f/d) – Computational Biology & Single-Cell Genomics – Decoding Brain Development at the Institute of Clinical Genetics The doctoral position is available as soon as
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solution to support such a demand by getting inspired by the brain’s powerful and energy-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization - from
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promising solution to support such a demand by getting inspired by the brain’s powerful and energy-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization
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Infrastructure? No Offer Description Area of research: PHD Thesis Job description: Your Job: Help us shape the energy transition! As part of your doctoral studies, you will support the development of innovative
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of optimization, inverse problems, or sensitivity analysis. Familiarity with surrogate models (ROMs, ML-based surrogates). Motivation for renewable energy and wind turbine technology. What We Offer Fully funded
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findings through functional laboratory experiments Developing and optimizing protocols involving omics methods, immune cell assays, and flow cytometry Close collaboration with biologists, clinicians, and
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
biology, in particular on single-cell genomics. We are looking for a highly motivated PhD Candidate (f/m/x) in Machine Learning (ML) or Computational Biology to join a collaborative research project with