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Field
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PhD in molecular biology, biochemistry, bioinformatics, genetics, proteomics, or related fields - Strong analytical and problem-solving skills - Excellent publication record in peer-reviewed
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Required Qualifications* PhD degree in bioinformatics Minimum 1 year of relevant experience Hands-on experience with R and/or Python and performing independent computational modeling. Ability to maintain
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Preparation of results for publishing and presentation at conferences Development of models for health and environmental impact assessment Your profile We are looking for a candidate with: PhD in the area of
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data and adjust recommend approaches to experimental design and analysis. Actively review new publications and adapt emerging methods and approaches to existing projects PhD degree in bioinformatics
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Researcher should have a PhD or a master’s degree in microbiology, computer science, or bioinformatics (or a related field). Prior experience in R and coding is expected. Experience in analysing high
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cutting-edge metabolomics, molecular/cell biology and bioinformatics approaches in a multi-disciplinary and collaborative team setting. Our lab is equipped with cutting-edge metabolomics, genomics
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Lexington, KY Type of Position Faculty Position Time Status Full-Time Tenure Track Status Tenure Track Required Education MD or PhD Degree Required Related Experience Research experience in computational
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Postdoctoral studies, employing Bioinformatic gene-expression analysis in Neurobiology (scholarship)
-profile papers, with national and international collaborations. The ideal candidates should hold a PhD in Bioinformatics, Computational Biology or a related field, with experience in omics data analysis
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involves novel bioinformatics approaches to study disease processes in the skin and to establish the determinants of inter-individual heterogeneity, including cross-species analytics, analyses of lncRNA
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patients with autoimmune disease. This research involves novel bioinformatics approaches to study disease processes in the skin and to establish the determinants of inter-individual heterogeneity, including