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using genetic data from family-based studies as well as -omics data for integrative deconvolution and machine learning methods for prognosis and therapeutic biomarker development. The collaborative
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a new generation of certifying combinatorial solvers, which output not only a solution but also a machine-verifiable mathematical proof that this solution is correct, has already led to several
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be required to spend negotiated periods of time at the Division of Robotics, Perception and Learning at KTH (Stockholm), and the More Lab (Lund) to collect and analyse data. What we offer Lund
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vegetation ecology, conservation or related areas Experience in programming using R or Python Good knowledge and experience in machine learning Experience in analyzing plant community, insect community and/or