339 computer-programmer-"https:"-"Inserm"-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Harvard University
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Qualifications: · Bachelor’s or Master’s in Engineering, Physics, Biology or related field. · Experience in biological imaging and image processing. · Ability to program. · Capable of organized, goal-motivated
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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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. Must be able to multi-task and perform duties with a high degree of speed, accuracy, and attention to detail. Must be proficient in writing business correspondence and have strong computer skills. Must
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and implementing commercialization plans for technologies in the physical sciences, engineering, applied, and computer sciences. This entails assessing the commercial potential and market opportunities
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Degree Master's degree strongly preferred Advanced biostatistics and epidemiology coursework are strongly preferred Experience with standard computer software such as Word, Excel, and PowerPoint
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contribute to technical deliverables and help to plan for technology translation. Basic Qualifications PhD in engineering, biomechanics, or a related field. Additional Qualifications Interest in
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plan to achieve strategic cultivation and solicitation of prospects. Work collaboratively to develop a multi-year plan that aligns with School fundraising priorities Provide regular updates on progress
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familiarity with generally accepted accounting principles is preferred. Must have excellent computer skills including in-depth understanding of, and experience with, databases, spreadsheets, word processing and
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. Some areas of particular interest include: genetics, evolutionary biology, neurobiology, developmental biology, and stem cell biology. Our lab uses both experimental and computational approaches
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flexibility, investment and planning under uncertainty, and the macroeconomic and policy implications of energy system transformation. Fellows will engage in rigorous empirical, computational, and theoretical