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Call for PhD Applications 14 Prestigious Marie Skłodowska-Curie Actions Double Degree Doctorate Fellowships GreenFieldData : IoRT Data Management and Analysis for Sustainable Agriculture Project 3
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of human cohorts” (65%, Proteomics Group) Ref. Number: 396_2026 PhD Position 3 “Image-based analysis of human cohorts” (65%, Lipidomics Group) Ref. Number: 397_2026 PhD Position 4 “Data Science” (100
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analysis, and/or optogenetic methods. Experience with developmental neuroscience, ion channel biology, mouse models, and quantitative data analysis is highly desirable. This Postdoctoral appointee may be a
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learning analysis of biomedical data and bioscientific programming for projects on neurological diseases. The candidate should have experience in the analysis of large-scale biomedical data (omics, clinical
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clubs. Depending on the program, lab rotations may be included. A distinctive feature is the triple-track system, enabling integration of basic research, clinical application, and patient-oriented data
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Developing solutions to integrate large foundation models
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the microbial communities responsible for dark carbon fixation at hadal depth. The focus will be on pelagic communities, but aspects of benthic chemosynthesis could be included. For further information please
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estimation, and the detection and compensation of sensor drift and degradation. The candidate will develop data processing and modelling approaches combining signal processing, statistical analysis, and data
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biomaterials, (9) Data-driven materials development, and (10) Advanced materials analysis technology. R26-01 Materials Science R26-02 Materials Science (for women) - Researcher [Field specified]: one position
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Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
analysis of parameterized finite‑element models. By integrating data‑driven and FEM‑based approaches, a hybrid model is developed that accurately represents physical relationships while providing real‑time