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coupled to operando analytics, e.g. ICP-MS. (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). Ideally, the applicant takes over the co-supervision of selected PhD candidates. We
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required Qualifications PhD in Chemistry Experience in preparative inorganic and/or organometallic chemistry Experience with functionalization and characterization methods Experience with inert-gas
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architectural surfaces, covering VNIR and SWIR spectral ranges. • Design and optimize HSI data-processing workflows, including spectral calibration, preprocessing, classification, and mapping. • Integrate HSI
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15.11.2025, Wissenschaftliches Personal For the Chair of Advanced Analytics in Manufacturing Management, which is part of the Heilbronn Data Science Center and the TUM School of Management
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and reality gap bridging for deformable object interaction (using environments such as MuJoCo, PyBullet, or NVIDIA Isaac Sim) Adaptive feedback control using learned and analytical models Physics
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Independently develop and implement research ideas within the VIOLET research framework Work closely with clinicians and data scientists to ensure the developed systems meet clinical needs and are validated
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analytical models Physics-informed machine learning for deformation modeling and prediction Integration of perception, planning, and control for robust real-time robotic performance Requirements Ph.D. in
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with large-scale data analytics frameworks (Hadoop, Spark, Flink, etc.) is desired - Interest in the development of software systems, very good knowledge and skills in programming with standard