71 structures-"https:" "https:" "https:" "https:" Fellowship positions at University of Oslo
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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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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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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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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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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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period at the University of Oslo. Place of work is Department of Informatics at Blindern, Oslo. Job description Unsupervised machine learning (ML) methods are widely used to explore structure in complex
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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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project will focus on reinforcement learning methods for generating complex structures with two possible application areas (i) the generation of virus capsids for gene therapy and (ii) the generation
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. Further information about the research groups can be found at: https://www.mn.uio.no/math/english/research/groups/algebra/index.html https://www.mn.uio.no/math/english/research/groups/geometry-topology
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. The research group has an excellent infrastructure, MiNaLab, covering chemical, structural, optical and electrical characterization methods, material growth, device fabrication and simulations. The student will