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needed. You have experience in advanced bioinformatic analyses of omics datasets, preferably single cell and/or long read RNAseq data. Demonstrable experience in advanced machine learning and/or high
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reliability. · Understanding of hardware accelerators for AI and their operation. · Familiarity with machine learning workloads (e.g., CNNs). As this is a research position, it is necessary
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in international research visits if needed. We are looking for a highly motivated researcher with: A PhD in machine learning, computer vision, remote sensing, glaciology, climate science, or a related
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Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing
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conceptual DFT (linear response function, Fukui functions) or QTAIM theory (delocalization index), and their validation on a set of compounds known from the literature - interfacing a MLIP (Machine-Learned
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PhD, MD/PhD, or equivalent degree in biomedical sciences (e.g., immunology, vascular biology, molecular biology, physiology). Computer Skills N/A Supervisory Responsibilities No Required operation of
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/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology, genomics, and epigenetics. Experience in next-generation sequencing
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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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(dark matter, baryogenesis) and machine learning applications in these topics. The University of Oregon also has an experimental high energy physics group involved in the ATLAS experiment at the LHC and
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Senior Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Doctoral Degree or foreign equivalent degree. Three years of research experience in machine learning and