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. Required Qualifications: PhD in statistics, economics, computer science, operations research, or related data science fields Strong data science skills, including experience working with large, complex data
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of two established fields emerges rich physics that is both fundamentally important but also has huge commercial potential. The group is currently 7 people large, with prospects of doubling in size by
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information about the role, please click the 'Apply' button above. Please ensure that you upload your Curriculum Vitae (CV), a covering letter and publications list in the upload section of the online
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, multi-billion investments will be made in large projects in Northern Sweden to create a fossil-free society both nationally and globally. Luleå University of Technology is involved in several
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 2 hours ago
well as on practically and industrially relevant research problems Extensive training and possibility to learn the cutting-edge experimental and data analysis methods. Access to world-class international large scale
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, and advanced data analysis. This role is part of a large-scale, multi-institutional consortium study aimed at uncovering novel insights into the genetic and molecular underpinnings of neurodevelopmental
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disease trajectories. The project is part of a Nordic initiative in large scale healthcare data analysis for development of precision medicine approaches. The researcher hired for this postdoctoral fellow
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the laboratory manager and Principal Investigator. 6. Mining large sequencing data sets Department Specific Qualifications Education: PhD in Molecular Biology, Immunology, Physiology or related field Experience
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
to submit a cover letter, curriculum vitae with full publication list, statement of research interests, a transcript and contact information for at least two references, all in PDF format. If you have any
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us to explore the relation between the degree and type of processing, and the foods that result from their use. The results will be used for data machine learning, in collaboration with other partners