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Vacancies Payroll- & Data Specialist To vacancy overview Apply now HR Finance Payroll- & Data Specialist This vacancy is only available in Dutch. Click here to view the vacancy in Dutch. Apply now Hi
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Information Website for additional job details https://www.academictransfer.com/363636/ Work Location(s) Number of offers available 1 Company/Institute Maastricht University Country Netherlands City
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, you’ll get hands on experience with lasers, interferometers, and precision optical alignment. Furthermore, you will develop valuable skills in experimental design, data acquisition electronics, and
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For candidates For employers For members AcademicTransfer Sign in Sign up en English (EN) Nederlands (NL) Alle vacatures Data scientist - NLP expert Deadline 10 sep ’26 gisteren gepubliceerd Vacature
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project is to detect cognitive strategies in single-trial EEG data. In very broad terms, we will use the HMP method ( https://github.com/GWeindel/hmp ) to discover cognitive operations in existing data
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Dutch university requirements for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious
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Royal Netherlands Academy of Arts and Sciences (KNAW) | Amsterdam, Provincie Noord-Holland | Netherlands | 19 days ago
you the chance to work with a wide range of neuroscience techniques, including data analysis, tissue staining , and postmortem MRI. What do we offer? You will be joining a highly collaborative research
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experimental data and contribute to innovative cancer research. Your responsibilities include: planning, preparing and performing molecular and cellular laboratory experiments; working with patient
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Royal Netherlands Academy of Arts and Sciences (KNAW) | Wageningen, Provincie Gelderland | Netherlands | 15 days ago
ecosystems across scales using hyperspectral earth observation data. Within the ASCENT project, you will work as a PhD candidate in an interdisciplinary consortium with remote sensers, ecologists, data
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explainable AI. A key challenge is that psychiatric research often relies on relatively small datasets, that while biomedical data are limited, and that data are subject to strict privacy requirements