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and well-structured PhD trajectory, the PhD fellow will be required to develop a career and competence development plan in dialogue with the supervisory team early in the appointment period. Aksel
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of Informatics at Blindern, Oslo. Job description Unsupervised machine learning (ML) methods are widely used to explore structure in complex and high-dimensional data, particularly in the life sciences, where
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surfaces and when actively driving a soft sheet near a wall. Essential to the projects is developing a new understanding of the fluid-structure interactions, that is to say, the coupling between hair’s
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of the Center for integrative neuroplasticity (CINPLA) and in the INTED center. This PhD project will focus on reinforcement learning methods for generating complex structures with two possible application areas
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the neuroscience work package which will investigate how HC use during adolescence influences structural and functional brain development and depression risk. Adolescence is a critical period of brain maturation and
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machine learning (ML) methods are widely used to explore structure in complex and high-dimensional data, particularly in the life sciences, where clustering analyses often form the basis for biological
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Is the Job related to staff position within a Research Infrastructure? No Offer Description We are investigating the roles of structural proteins of the cell nucleus, nuclear lamins, in breast cancer
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English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements
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and possible exemptions can be found here: https://www.sv.uio.no/english/research/phd/structure/programme-description.html#two Desired qualifications Experience with statistical genetics, polygenic
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requirement: Good oral and written communication skills in English English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english