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agronomic datasets from cover crop experiments using advanced statistical and quantitative genetic approaches. Apply genomic prediction methods to evaluate and improve cover crop performance. Design
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. ● Contribute to open-source code and reproducible pipelines. Basic Qualifications ● PhD (completed or near completion) in Statistics, Biostatistics, Data Science, Computer Science or a closely related field
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to multitask Flexibility with work schedule to meet study demands Preferred Qualifications: MD or PhD in relevant field Minimum 1 year preferred Skill in collecting, organizing, and analyzing data. Ability
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Qualifications: A PhD, MD/PhD, or equivalent research doctoral degree in neuroscience, biomedical data science, computer science, psychology, psychiatry, statistics, engineering, applied mathematics, or a related
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chance for multiple years of renewal based upon mutual agreement. Requirements A PhD in Computational Biology or Systems Biology is required. The successful candidate will have a strong foundation in
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multiple years of renewal based upon mutual agreement. Requirements A PhD in Bioinformatics, Computational Biology, Systems Biology, Genomics, Data Science, Molecular Biology, or a closely related field is
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does not permit remote work. This is a term appointment funded for one year from the date of hire with an excellent chance for multiple years of renewal based upon mutual agreement. Requirements A PhD in
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methods with the ability to implement and evaluate machine-learning systems at scale. Candidates may come from topological data analysis, geometric deep learning, network science, statistical physics
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field of research Participate in education, and PhD and master student supervision Profile Strong background in computational biology, bioinformatics, machine learning, or a related quantitative field
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Mathematics of Symmetry and Computation (CMSC) is a globally recognised research centre within the Department of Mathematics and Statistics at The University of Western Australia. CMSC brings together leading