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Field
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). The successful candidate will be involved in projects to perform big-data research, bundling genetics, multi-omics, biomarker, clinical, and histopathological data, to harness the full range
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analysing large data sets, generated from electronic health records. Experience of supervising research internships or other student activity is desirable. Diversity Committed to equality and valuing
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the analysis of large, integrated health-related clinical and administrative datasets, national surveys, and other data. Statement Posting Details Special Instructions to Applicants Quick Link to Posting https
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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15 Jul 2026 Job Information Organisation/Company Wageningen University & Research Research Field Chemistry » Analytical chemistry Chemistry » Biochemistry Researcher Profile Recognised Researcher
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together leading European partners to investigate early-life determinants of immune system development through large-scale, longitudinal multi-omics studies, integrating data across multiple birth cohorts
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German Cancer Research Center in the Helmholtz Association (DKFZ) | Oettingen in Bayern, Bayern | Germany | 3 months ago
Molecular mechanisms of cancer metastasis Computational large-scale data integration Your Profile Master’s or PhD degree in bioinformatics, computational biology, genetics, molecular biomedicine, cancer
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and transcriptional regulation, Imaging and large-scale data analysis/Bioinformatics, and Epithelial biology. Required Qualifications: Ph.D. (or equivalent) in Molecular Biology, Cell Biology, or
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for analysis of health record data for patient diagnosis and outcome prediction. Perform large-scale querying and analysis of clinical health record databases. Engage with clinical collaborators, to place the
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integrates neuroimaging, sleep measurement, digital phenotyping, electronic health record (EHR) data, and deep clinical phenotyping to identify predictors of symptom trajectories and functional outcomes in