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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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sequencing data is an advantage. We offer: A three-year PhD position (or four-year for Master students) in a supportive, stimulating, and interdisciplinary research environment Enrollment in PhD school
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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. The successful candidate will work on field-based experiments, data collection, and analysis, focusing on understanding the interaction between floral resources, pollinator activity, and apple yield outcomes
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degree in (analytical) chemistry, biochemistry, or a related discipline Hands-on experience in mass spectrometry-based proteomics (e.g. DDA, DIA, PRM) Experience with proteomic data analysis Computer
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architectures, and on-device inference on edge-compute platforms. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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University, Faculty of Chemistry - more information about the PhD program at the HZDR can be found here Salary and social benefits in accordance with the collective agreement for the public sector (TVöD-Bund
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Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities
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emerging types of national emergencies and evaluate their spatial and operational implications. This will include an analysis of UK population distributions, terrain, infrastructure access, and airspace