361 computer-programmer-"https:"-"UCL" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "P" uni jobs 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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. 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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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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Candidates MUST meet the following basic qualifications in order to be considered for this role: A minimum of five years of progressive administrative and/or project coordination experience. Computer skills
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engineering fields. The AM/SEAS community of scholars also endeavors to educate the next generation of scientists and engineers with a view towards developing applications with strong mathematical and computing
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degree preferably in finance or accounting. Exceptional customer service skills required. Must be able to effectively communicate (verbal and written). Computer proficiency in Excel and Word with a strong
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skills. Solid computer skills such as proficiency with Microsoft Office; intermediate to advanced Excel skills required. Demonstrated knowledge of financial principles, budget management, and financial
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. Qualifications Basic Qualifications: Minimum of seven years’ post-secondary education or relevant work experience Master’s or PhD in one of the following disciplines: Computational Sciences in either Physics
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research associates to develop and apply theoretical and computational approaches to study complex cell biological systems. The emphasis will be on combining statistical inferences and biophysical modeling