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REQUIRED QUALIFICATIONS: PhD in Bioinformatics, Computational Biology, Physics, Computer Science or related field. Provide best-¬practices data analysis, including QC and visualization, employing common NGS pipelines such as RNA¬seq, ChIP¬-seq, ATAC-seq, Methyl-seq, DNA¬-seq, and Microbiome Sequencing.
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Conveyance systems, including wire-to-water analysis, pumping optimization, transient analysis, computational fluid dynamics (CFD), and management of physical modeling projects. Conveyance systems, including wire-to-water analysis, pumping optimization, transient analysis, computational fluid dynamics (CFD), and management of physical modeling projects.
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Nobell is seeking a Computational Biologist / Machine Learning Scientist to join our team of scientists to contribute to the development of the Nobell Plant Grown Protein (PGP) platform. Drive computational analysis in collaboration with wet-lab scientists to optimize molecular biology workflows and molecular designs in plants.
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Experience in programming languages used for data manipulation and computational statistics (Python, R, MATLAB, C. Proficiency in programming computational and statistical algorithms for large data sets.
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The Computational Fluid Dynamic Engineer will lead the creation and development of computational fluid dynamics (CFD) design models. Strong computer skills include AutoCAD, BIM (Revit), 3D Rendering Programs, hydraulic analysis, and HVAC analysis programs.
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Ph. D. in Statistics, Applied Mathematics, Biomedical/Chemical Engineering, Computer Science, Physics, Computational Biology, or related field. Family care services such as adoption and surrogacy reimbursement, fertility/infertility benefits, support for traveling mothers, and child, elder and pet care resources.
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Computational chemistry/materials modeling using one or two of the electronic structure theory-based codes are essential. Argonne National Laboratory in Lemont, IL is seeking a Postdoctoral Appointee in the Materials Science Division in Computational Materials Chemistry and Machine Learning.
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Minimum of 5 years of demonstrated experience using computational fluid dynamics (CFD) analysis tools [Ansys, COMSOL, SimFlow, or similar] for R&D and new product development. Minimum of 10 years demonstrated engineering R&D experience in the development of fluid systems, hydraulic systems, computational fluid component selection, sizing, and custom designs.
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Requirements: Bachelor's or Master’s degree in bioinformatics, Computational Biology, Biological Sciences, or a related field. We are searching for a talented Bioinformatics Analyst to join our team.
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We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics.
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Postdoctoral associates independently choose their (computational and biomedical) mentors from Broad-, MIT-, or Harvard-affiliated faculty. The Schmidt Center’smission is to create the theoretical, computational and algorithmic paradigms that will enable us to understand the programs of life and how they connect across scales, from proteins to cells to tissues and organisms.
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Experience in microfluidics systems and other computational approaches is a plus. Adjunct Associate Professor of Cell and Developmental Biology, Vanderbilt University) and participate in the nationally.
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Strong background in genomics, bioinformatics computer science, bacterial or viral genetics, and/or computational biology. Candidates must have completed a Bachelor's or Master's degree from an accredited US university, or international university of equivalent standard, in Bioinformatics, Computer Science (combined with experience or education in biology or bioinformatics), Computational Biology, Mathematics or a closely related area.
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Experience in numerical modeling based on Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) (convergence, discretization, meshing). and correlate with computational results.
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BS, MS or PhD degree in electrical engineering, computer science, or related fields (e.g., physics, applied biology, computational design, biodesign, robotics) This person thrives at the intersection of electrical design, software, firmware, printed circuit board (PCB) design, and sensor integration, grounded by a strong foundation in physics, mathematics, and core engineering disciplines.
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