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develop computational methods that connect human genetic variation to biological function. Using population-scale human genetics together with single-cell, spatial, and multimodal molecular data, you will
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collaborative discussions. You must hold a PhD/DPhil in Statistics, Statistical Machine Learning, Deep Generative Modelling, or a closely related field, together with relevant postdoctoral research experience
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, mathematics, computer science, engineering or a related discipline Required Other None Additional Preferred Experience working in one of the following areas: Machine learning/predictive modeling
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19 Sep 2026 Job Information Organisation/Company University of Oulu Research Field Biological sciences » Other Computer science » Other Mathematics » Statistics Medical sciences » Other Researcher
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analysis Large language models or machine learning/predictive modeling for longitudinal data analysis Strong computer programming skills Strong mathematical or statistical skills Ability to work as a part of
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beginning in fall 2026, preferably with an interest or focus on statistical foundations of data science, artificial intelligence and machine learning, theoretical statistics and probability, uncertainty
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Intelligence and Machine Learning, Computational Statistics, Random Matrices, Free Probability, Stochastic Control, Mathematical Finance, Stochastic Partial Differential Equations, Markov Processes, Branching
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computer software; Assisting with preparing grant applications to secure further funding for relevant projects; Helping establish new projects and research consortia relating to the Zuccolo Group research
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. For applicants to the Microbial Bioinformatics track: PhD or equivalent in Computational Biology, Microbiology, or a related field. At least one published contribution in computational biology, microbiology, or a
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“3Ds of 3D: Design, Data quality and Data driven decisions - Advancing statistical methods for human 3D movement analyses of clinical populations”, which aims to develop, evaluate, and implement