79 data "https:" "https:" "https:" "https:" "Dr" "L2CM" Postdoctoral research jobs at Aarhus University
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partners. At same time, XJTLU is exploring future education by blending the educational theory, best practice and culture from west and east. For detailed information about the university, please visit
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scientific journals Research experience in some of the areas of fungal transformation, CRISP/Cas9 modification of fungal genes, analysis of metabarcoding data, and soil microbiology. Additional qualifications
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. The research project consists of studies that will be based on data from the Danish National Birth Cohort and the National Child Health Register. Your job responsibilities As Postdoc in Epidemiology your
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by
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a focus on metabolomic and transcriptomic data. Performing tissue sectioning, matrix coating of the resultant sections, data acquisition using a Bruker TimsTOF MALDI-2 instrument and downstream
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research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and
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. Consequently, your employment will as of that date be with a department. Contact information For further information, please contact: Assistant Professor Emil Laust Kristoffersen, +45 29271306, emillk
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include psychiatric disorders as well as clinical and social outcomes, but specific tasks may depend on applicants. The positions will generally involve various data analyses using Danish register data and
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Electrophysiological characterization of muscle fiber excitability (in collaboration with the research group) In vivo studies using animal models of neuromuscular disease Integration of molecular and transcriptomic data