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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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research school. Data driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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degree in relevant fields (bioinformatics, immunology, computational biology, mathematics, and/or statistics). Strong programming skills in R and/or Python Demonstrated strong ability in analyzing high
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relevant fields of biology (e.g., systems, evolutionary, developmental, computational), physics, mathematics or related fields. In the appointment process, special attention will be given to research skills
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. The PhD position is within the Data-driven life science (DDLS) Research School. DDLS uses data, computational methods and artificial intelligence to study biological systems and processes at all levels
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substantially equivalent knowledge in some other way. For this position, the applicant must hold a master’s degree in molecular biotechnology, bioinformatics, computer science, or another area that the employer
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. To meet the general entry requirements for doctoral studies, you must: Hold a Master’s degree in computer science, image analysis and machine learning, engineering, data sciences, applied mathematics
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in computer science, engineering, data sciences, applied mathematics, machine learning, or another related field; or Have completed at least 240 credits in higher education, with at least 60 credits at
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science. We are looking for a candidate with a PhD in either engineering/computer science/physics/mathematics. Experience with ML implementation (ideally interpretable ML and/or generative AI) is required
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at developing and applying computational tools to understand the evolution of biodiversity (see https://islandevolution.github.io/ ). As a postdoc in this project, you will work with mathematical modelling