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=VUdBLjQ4NzUzLjk5MDhAdWdhLmFwbGl0cmFrLmNvbQ Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications mechanics, signal processing, field work, laboratory experiments, theoretical modelling, rivers
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, etc ... Each phase of the selection process will be reported on the website where the offer is published. If applicable, indicate your request. Finally, the name of the person selected will be published
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Researcher (R2) Positions Postdoc Positions Application Deadline 31 Oct 2026 - 23:59 (Europe/Warsaw) Country Poland Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Jan
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development, spin simulations, or MR signal modeling is highly desirable. Strong programming skills, for example in Python, MATLAB, C/C++, or a comparable scientific computing environment. Experience with
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the human musculoskeletal system, or experience providing engineering, hardware, statistical, or algorithmic support for such research (e.g., in biomechanics, biomedical signal processing, analysis of data
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=VUdBLjQ4NzUzLjk5MDhAdWdhLmFwbGl0cmFrLmNvbQ Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications mechanics, signal processing, field work, laboratory experiments, theoretical modelling, rivers
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concepts in plant-pathogen interactions; contribute to the funding of the group; contribute to (coordination and innovation of) teaching and supervision of PhD students and postdocs; develop (inter)national
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this knowledge. In previous roles you have worked with the application of data science and artificial intelligence in the context of biomedical signals. You enjoy the process of conceiving and writing papers (in
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portfolio of activities for a research program, inform or influence policy and processes, and engage the public as partners in biomedical and behavioral research. An initial review of applications
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. The project will focus on integrating quantitative and textual information, accounting for structural shifts in measurement processes over time, and developing scalable inference for high-dimensional settings