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Position #00843047 – Requisition #39319 Job Summary: The Department of Medicine, University of Colorado School of Medicine and Department of Biostatistics and Informatics, Colorado School of Public Health is
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Laboratory is a world leader in catalysis, polymer upcycling, separations, computational chemistry, rare earths, quantum materials, synthesis, and additive manufacturing. Ames Laboratory is the leader
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skills. Strong attention to detail and good organizational skills. Strong desire to work in a collaborative research program. Interested candidates should email Professor Michael Manfra at mmanfra
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artificial intelligence with a preferred focus on computer vision and medical image analysis. Preferred Qualifications: PhD in Medical Physics, Bioengineering, Biomedical Engineering, Physics, Computer Science
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linear, mixed-integer, and stochastic programming. Work with programming languages such as Python, Julia, or C++ to build robust analytical tools and perform large-scale data analysis. Collaborate with
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activity. · Computational or bioinformatics experience for analysis of omics data. Required Application Materials: 1. Cover letter describing your background, programming experience, and research interests
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wellbeing program Financial counseling services Employee Assistance Program with eight sessions of counseling at no cost How To Apply Applications must be submitted online. To be considered for this position
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, strong research background in statistics and ML, programming, data analysis, strong genetic and genomic knowledge, as well as good written and oral communication skills. Additional Qualifications Special
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Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division, Computing and Computational Sciences Directorate, at Oak Ridge National Laboratory (ORNL). This position presents
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analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division, Computing and Computational