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Field
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Summary The Behrend Memorial Travel Scholarships is offered to student who are enrolled in the Master of Science in Mathematics and Statistics and are undertaking travel associated with research and study
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– Academic performance in subjects related to data processing and analysis in a clinical context. VII.II- I – In the evaluation of the interview, candidates' performance will be assessed according
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%)Analysis of grades obtained in curricular units relevant to the work to be developed. (40%)Analysis of the candidate's motivation. (20%) Composition of the Selection Jury Jury President: Marcelino Bicho dos
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applicants will be supported in applying for a Study Permit. We are currently looking for students to work in two main areas: 1) PhD in Modelling microbe-molecule interactions for climate change Human-driven
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/F) Call open for applications for a research grant within the framework of project “FIBERNEST XL - LARGE FIBER LASER CUTTING EQUIPMENT WITH AUTO-NESTING”, with nr. 20436 and operation code
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Status: Open Applications open: 15/05/2024 Applications accepted at any time View printable version [.pdf] About this scholarship Description/Applicant information Unpinning “the role of microbes in
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25 Nov 2025 Job Information Organisation/Company University of Porto Department Human Resources Department Research Field Computer science Mathematics Researcher Profile First Stage Researcher (R1
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the field of Life/Health Sciences or Toxicology; • Experience in cell culture, handling of human biological samples as well as questionnaires; • Laboratory experience in the analysis of cellular
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. 3. Parameterization of the power electronics converter for operating the three-phase induction motor in speed modes. 4. Implementation of a laboratory test bench and performance of tests. 5. Analysis
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Freiberg, Sachsen | Germany | 20 days ago
rigor # Proficiency in Python (or Julia/R) for data handling, ML model development, and statistical analysis # Ready to work with time‑series data, sensor fusion, and feature engineering # Very good