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Field
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welcomes applications from individuals with a master’s degree in the following fields: Computer Science Mathematics Natural or engineering sciences or an equivalent degree, interested in High-Performance
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cancer cell plasticity in AML. Our overall goal is to pave the way for new cancer therapies. The aim of this PhD position is to perform and to functionally and molecularly characterize multiomics single
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outstanding key performance indicators. Your tasks in detail: Contribute to develop an innovative process for the autothermal dehydrogenation of LOHC using fundamental knowledge of chemical engineering
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of structure-performance relationships of different catalyst and membrane surfaces Development and validation of various test stand modifications Coordination with internal and external project partners from
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on methods development in machine learning, uncertainty quantification and high performance computing with context of applications from the natural sciences, engineering and beyond. It is embedded in
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nitrogen fixation at the molecular level. Your Responsibilities: Perform EPR and related spectroscopic investigations of biological and synthetic nitrogenase systems Prepare synthetic iron-sulfur clusters
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for an ideal balance between stability, performance and price Building a test station for evaluation of electrochemical performance in short stack Physical, spectroscopic, and electrochemical characterization
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control software and machine learning expert. How you will support us: ▪ You will take on responsibilities in the field of control and operation of high-coherence superconducting quantum circuits, with a
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for carbohydrate analysis using ion chromatography (e.g. HPIC, HPAEC-PAD, LC-MS) and preparative column chromatography Planning and carrying out sampling as part of field campaigns Independent performance