71 engineering-in-image-processing-"MONASH-UNIVERSITY" PhD positions at Technical University of Munich
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Chair of Biological Imaging 07.08.2025, Wissenschaftliches Personal We are now looking for a highly qualified and motivated researcher with an engineering or physics background (f/m/x) and a
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Natural Language Processing (NLP) und Software Engineering mit Fokus auf medizinische Anwendungen. Leitung interdisziplinärer Projekte mit Experten und Expertinnen aus Wissenschaft und Medizin
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well as data processing meth-ods for analyzing block-like structures made of limestone and granite, Evaluation of data using acoustical imaging techniques and passive seismic monitoring, Carrying out
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of Engineering and Design. Our teaching and research focus lies on computer-based development of engineering products, particularly on the planning and realization of built facilities using computational modeling
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clinical use-cases for benchmarking existing state-of-the-art (SOTA) Federated Learning algorithms. This includes running a few pre-processing pipelines. Develop SOTA FL algorithms that tackle data
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(SOTA) Federated Learning algorithms. This includes running a few pre-processing pipelines. Develop SOTA algorithms in Robustness against data and model poisoning attacks. Develop SOTA algorithms in
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Engineering, Operations Research, Civil Engineering, Computer Science, Data Science or a related field, from a university/department with a strong international research reputation Strong mathematical and
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science, physical chemistry, materials science, or materials engineering, or a closely related field • Experience with cellulose and its processing technologies is an advantage • Strong willingness
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• Eukaryotic cell culture and transfection of cell lines • Handling and experimental use of organoid models (provided by a partner institute), including adaptation for biophysical assays and imaging
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, Computational Linguistics, Data Science or a similar field Good theoretical knowledge and practical experience with Natural Language Processing (rule-based and/or machine learning) Software Engineering Motivation