28 machine-learning-phd-in-denmark Postdoctoral positions at University of Washington
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analysis; Biomarker identification through the use of machine learning approaches; and Multi-omics data integration with genomics, transcriptomics and methylomics data. Job Description Primary Duties
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is 7/1/24. Qualifications Completed PhD or a foreign equivalent. The current project seeks to revolutionize the entire process from data to prediction with a paramount focus on reproducibility and
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. For more information, please visit the University of Washington Labor Relations website. Qualifications Minimum Qualifications * PhD awarded by the start date in a relevant field, such as library and
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activities and psychological stress. Duties/Responsibilities The researchers will contribute specifically through: Gathering data, developing and implementing machine learning models, and interpreting findings
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learn advanced instrumentation, 3D data analysis, and AI methods in close collaboration with engineers and physicists. We work closely with lab members to develop the skills, confidence, and creativity
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interpreting wet-lab synthesis data are encouraged to apply and will have opportunities to explore machine learning-guided approaches in chemistry. In addition to excellent research skills, we are seeking
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experiments and publish papers, under the supervision of the PI on a project in the broad area of epithelial cell mechanobiology. Mentor PhD students, assist in lab organization, and perform lab duties as
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, and use deep learning to gain insight into biological processes. You will also gain direct exposure to cardiovascular physiology and rodent imaging in close collaboration with biologists. We work
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Qualifications: PhD in Environmental Engineering, Environmental Chemistry, Analytical Chemistry, Environmental Science, and/or other aligned discipline. Operation and optimization of LCMS and/or GCMS
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. Experience with high-throughput molecular biology assays. Experience with complex functional experiments. Background in machine learning, AI, or data integration for genomic datasets. Familiarity with gene