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Website https://karriere.norceresearch.no/en/jobs/7235739-phd-research-fellow-in-data-a… Requirements Research FieldMathematics » Applied mathematicsEducation LevelMaster Degree or equivalent Skills
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analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks on material design by using PyTorch or Matlab PLEASE
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Experience or competence in heterologous production of enzymes is an advantage Teaching experience is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good
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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
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insights into fuel–air mixing, spray break-up, heat release, soot formation, and in-cylinder flow structures. Your immediate leader will be Professor Terese Løvås. About the project The PhD project will
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symposium June 10-11, 2026 (hybrid physical/digital event, see details at uit.no/project/arcticmsca/program-structure ). At this event, the candidates will present their past research achievements, discuss
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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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you are able to: Work independently Work in a structured way, set goals and make plans to achieve them Work in a team, present and discuss your research with other professionals Work constructively
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has access to excellent HPC infrastructure. For more information about LTG, please see: http://www.mn.uio.no/ifi/english/research/groups/ltg/ The successful applicant will benefit from close
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is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills. Applicants must have good written and oral English skills. Personal