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. Analyzes large data sets. Analyzes next generation sequencing data (e.g., RNS-seq, whole genome/exome sequencing). Uses state-of-the-art bioinformatical and statistical tools. Develops new statistical
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research environment supported by a team with broad expertise in data science, infectious diseases, hepatology, and clinical informatics. You will take a leading role in analysing large-scale, longitudinal
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of large-scale infrastructure on fish connectivity and populations by advancing our understanding of critical ecological processes within these modified coastal seascapes. The project expects to generate new
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/genomics Experience with the analysis of large-scale genomic data Demonstrated ability to summarize scientific findings in the form of written manuscripts and oral presentations Desired Qualifications
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data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San
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well as in a team. Experience in healthcare data analysis and related track records of publishing academic research papers is highly preferred. The appointee will work on healthcare big data related project
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laboratory techniques Thorough knowledge of population genetics/genomics Experience with the analysis of large-scale genomic data Demonstrated ability to summarize scientific findings in the form of written
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Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate predictions Ability to work in a team Ability to communicate orally in
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genomics, with cutting-edge methods, large data sets and good resources A creative role combining a high degree of autonomy with mentorship from Dr. Lappalainen and interactions with colleagues in the lab
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Description Job Responsibilities -Analyze and interpret metagenomic data to investigate and identify often divergent viral genome sequences. -Collect, reconstruct and analyze large datasets obtain by cryo