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Field
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live in. Your role We are seeking a highly motivated PhD candidate to research how artificial intelligence (AI) techniques can help software engineers formally specify and verify software systems. State
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Research Asst/Assoc/Full Professor, Department of Biostatistics, Health Informatics and Data Science
biomedicine. The ideal candidate must hold a PhD and possess strong methodological expertise in areas such as generative AI, machine learning, decision support methods, and the evaluation and validation of AI
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Research Asst/Assoc/Full Professor, Department of Biostatistics, Health Informatics and Data Science
, research associates and faculty. Minimum Requirements PhD degree with formal training in at least two of the following areas: biostatistics, data sciences, computational methods, knowledge retrieval
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University, to study the cytoskeleton and transcriptome of the shoot meristems and developing flowers of Arabidopsis thaliana by optical microscopy, and to develop as the highest priority methods of tissue
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taxonomy and research data management. You communicate with service providers in the industry and organize taxonomic services and method transfers. Active participation in the application and implementation
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theoretical and practical sport science. Our Bachelor's degree, Master's degree and PhD programmes aim to be of great relevance. NIH has approximately 1300 students and a staff of 240 in four departments, six
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Published Monday 12 May 2025 Deadline Monday 12 May 2025 Work area PhD Organisational unit Rotterdam School of Management (RSM) Salary € 2.901 - € 3.707 Employment 1 fte - 1 fte Abstract This PhD
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• A PhD degree is a plus but not a formal requirement. Information and application For more information about these positions please contact Prof. Nynke Dekker, e-mail: nynke.dekker@physics.ox.ac.uk
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the Dean of the Faculty and pending student enrollments, the successful candidate will be asked to teach 2-3 courses in AY26, on campus, in areas such as American Politics, Comparative Politics, Formal
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microarchitectural vulnerabilities and/or formally prove the robustness, for a given fault model, of various RISC-V based processors. We have also developed binary-level program analysis methods (BINSEC/ASE) able