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and as part of a team Research Fellow (PhD level) PhD degree in topic covering in Plant Biology, Bioinformatics,2 Data Science, Statistics, Image analysis Demonstrated experience in plant phenotyping
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Responsibilities: Design, execute, and manage independent research projects from conception through data analysis and manuscript preparation Conduct experimental research to a high standard in accordance with
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(e.g., mouse systems) Integrate biochemical findings with cellular and physiological outcomes to address disease-relevant questions Independently plan and lead research projects, including data analysis
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. transformer models). One focus of this work will be on B-cell receptor evolution. Experience in applications of modern machine learning methods as well as in biological data analysis are needed for the position
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the master's degree has been awarded. Documented experience from or competence in radiation detectors (design, construction, operations or data analysis) is a requirement. A general knowledge of programming
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, Java) with proficiency in a Linux environment. Experience with computational pipeline development. Statistical analysis and data visualization skills. PhD Michigan Medicine conducts background screening
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The appointment is made in accordance with State regulations and guidelines at UiT. At our website, you will find more information for applicants . Remuneration for the position of PhD Fellow is in accordance with
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Responsibilities: Develop chemical and biochemical assays and analyses, conduct comprehensive laboratory experiments, data analysis and reporting. Design, develop, and test microfluidic devices for miniaturised
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, hematology, or immunology research. Ability to conduct research independently and work collaboratively with other scientists. Strong data analysis and writing skills. Interested candidates should email their
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statistical analyses of individual trajectories and variability preparation of scientific publications based on the KVIKK dataset The project combines ongoing data collection with analysis of existing data