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Field
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healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics
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qualification in Genetics, Bioinformatics, Computer science, Data science, Statistical Genomics or a related discipline involving the interrogation of ‘omics’ datasets. Hands-on experience with large-scale human
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collaborate with an interdisciplinary team of researchers consisting of Clara Ekerdt, Guillen Fernandez, Gabi Janzen, Evan Kidd, Kristin Lemhöfer and James McQueen. This team have been working on a large-scale
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training students Maintain analytical equipment Cooperate with other large collaborative projects of the research group Qualification: Required: A diploma and a PhD in microbial natural product chemistry
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of the extracts; LC-MS and bioactivity-guided isolation and structure elucidation of the purified metabolites Supervising and training students Maintain analytical equipment Cooperate with other large collaborative
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programming language (R, Python, or Perl) and experience working in Linux and/or high-performance cluster environments. A strong ability to perform analytical reasoning to extract biological insights from data
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research focused on advancing Precision Menopausal Hormone Therapy (P-MHT) for women worldwide. Integrate and analyze large-scale human datasets, including electronic health records, claims data, and omics
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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University as well as with key stakeholders from the National Forest System and state level entities. The postdoc will generate large genome-scale datasets with a variety of techniques such as Genotyping by
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programming language (R, Python, or Perl) and experience working in Linux and/or high-performance cluster environments. A strong ability to perform analytical reasoning to extract biological insights from data