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development skills using C/C++ and Python programming languages, with experience developing, validating, debugging, and evaluating research software. Demonstrated record of conducting independent research and
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knowledge of English, 5. publication achievements (preferably international), 6. teamwork skills – openness, tolerance, good communication skills, 7. Candidates must meet the criteria specified in the terms
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, with UW licenses). Interviews will be conducted in English. The candidate will receive an invitation to the interview by e-mail at least 5 days before the proposed date. If a candidate is unable to
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of detailed curriculum vitae structured according to the items under point 5; c) Other documents that are relevant for the evaluation of the qualification in related scientific areas; d) Any other documents
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++ or a comparable scientific-computing language, with evidence of producing reliable research code. 5. Ability to carry out independent numerical research, validate results and communicate technical
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in Zintellect, they must click the unique link in each email request, but will be given the opportunity to copy over what they had previously submitted. All documents must be in English or include
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, gene editing and AI-based approaches to understand gene regulation. Working language is English. We offer a well-equipped, international and scientifically stimulating environment for postdoctoral
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provide meaningful explanations of their predictions to downstream users. A central aim of this project is to investigate how Vision-Language Models (VLMs), Multimodal Large Language Models (MLLMs), and
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/ektx4WpIkRxQshUAEfpDj1L6bQihLRRj/en?csid=5… Requirements Research FieldChemistry » Inorganic chemistryEducation LevelPhD or equivalent Skills/Qualifications Applicants must hold a PhD in Chemistry, Inorganic Chemistry
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods