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Field
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scales. The successful candidate will contribute to cutting-edge research at the interface of bioimaging, data science, infection biology and immunology, supporting the quantitative analysis of complex
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of these approaches quickly, in a data-based and reliable manner. Your main tasks include: Method development: you compare and decide on methods of Machine Learning (ML) and Artificial Intelligence (AI), such as
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which technology and research fields are advancing. Furthermore, you will also extend the indicator beyond novelty toward quality assessment and validate the reliability, robustness, and fairness of LLM
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for the acquisition, processing, and analysis of physiological signals and vital parameters (e.g., respiration, cardiac activity, motion) Application and advancement of methods in digital signal processing, statistical
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(DNA, RNA, and protein purification, PCR methods, Western Blot, etc.) and experience in cell and molecular biology work under S1/S2 conditions (cell culture, microscopy, FACS analysis and sorting) Good
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, provided that completion in the near future can be reliably demonstrated. Demonstrated scientific expertise in machine learning and deep learning. Knowledge of explainable AI (XAI), uncertainty analysis and
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mathematical background Core skills: Probability and statistics. Estimation, Bayesian inference, uncertainty quantification and calibration (proper scoring rules, reliability diagrams, ECE), experiment design
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and analysis of measurement results in the context of the development of simulation methods and software What you contribute Currently studying engineering or natural sciences Good written and spoken
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analysis and relevant scientific software or programming languages Experience in diagnosing methodological, instrumental problems and developing robust solutions Scientific independence, creativity
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data sets for automated preliminary design, generation of missing data, and provision of a database suitable for ML/AI evaluation. AI-supported evaluation and automated analysis of engine concepts