286 computer-science-programming-languages-"the"-"FEMTO-ST-institute"-"U.S" PhD positions in Netherlands
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will design, implement, and evaluate, within the framework of Design-Based Research, a professional development programme that supports STEM instructors in using AI effectively and critically in
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diverse range of nationalities, and an active visitor program which attracts the best string theorists from all over the world. Our group's faculty members include: Jay Armas, Daniel Baumann, Jan de Boer
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), or an equivalent - or are preparing to obtain such a degree elsewhere, in principle cannot be admitted to the doctoral programme at EUR. Employment conditions and benefits What do we offer: A fully funded 4,5 year
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Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a: PhD Candidate in AI for Network Analysis (1.0 FTE, 4 years) About this position
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the next three years is to be expected. A university PhD training programme is part of the agreement and the candidate will be enrolled in the Graduate School of Science and Engineering. Application Do you
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) Good communication skills in English Ability to work efficiently, both independently as well as in a team Previous experience in the fields of soft matter or biophysics, quantitative image analysis and
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) Good communication skills in English Ability to work efficiently, both independently as well as in a team Previous experience in the fields of soft matter or biophysics, quantitative image analysis and
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period of 4 years at the Eindhoven University of Technology, Department of Mathematics and Computer Science. The student’s working locations will be at Eindhoven University where the PhD candidate will be
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communication skills in English. Strong affinity with philosophy of science and scientific methodology. Expertise on, or a strong interest in medical science as application domain. Working knowledge
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(spoken and written). Preferred qualifications Prior experience with 3D cell culture, organoids, CRISPR-Cas9, or imaging-based phenotyping. Familiarity with transcriptomics or basic computational biology (R