35 computer-programmer-"https:"-"CNR"-"https:"-"https:"-"https:"-"IFM" Fellowship positions at University of Michigan
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research that together enhance our contribution to society. Job Summary The Najarian Lab in the Gilbert S. Omenn Department of Computational Medicine & Bioinformatics is seeking a Research Fellow to lead
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fragmented genomic data; Experience working with herbarium data; Strong bioinformatics skills; Strong biodiversity informatics skills; Knowledge of phylogenomics and population genetics; Knowledge of plant
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that target dental pathogens. The successful candidate will have opportunities to interact with external collaborators, such as computational biophysicists or medicinal chemists. The position would be ideal
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. Analyze and interpret data using appropriate computational/statistical approaches; maintain reproducible workflows and clear documentation. Write manuscripts and present findings; contribute to grants
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functional MRI (fMRI), electroencephalography (EEG), and neuromodulation with low-intensity focused ultrasound (LIFU); computational analysis of fMRI and EEG data; development of new research methodologies
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, solid mechanics, and the dynamic of locomotion on soft substrates A strong background in computational research using Discrete Element Method and continuum mechanics simulations is preferred, while
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. Experience working with medical images. Very good computer programming skills and physics background is essential. Desired Qualifications* Nuclear medicine imaging/dosimetry experience. Experience in image
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values are Compassion, Leadership, Excellence, Responsibility, Trust, Creativity and Inclusion. U-M offers comprehensive benefits to help you stay well and to support you as you plan for a secure future
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applications Human-centric and sensing-enabled mechanical systems Strong background in computational modeling and analysis, including finite element analysis (FEA), multiphysics simulations, and data-driven
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. Must have experience with analysis of sequencing data (RNA-seq, CUT&RUN, etc) and/or sufficient computation background to learn these analyses. Must have a strong publication history supporting potential