235 computer-programmer-"https:"-"UCL" "https:" "https:" "https:" "https:" "https:" "Dr" "FEUP" research jobs at Harvard University
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for analysis (e.g., text manipulation); One or more computational environments for statistical analysis (e.g., MATLAB, Stata, R, or Python); Creating and managing very large datasets; Managing and mentoring
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What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
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, and light scattering) with modeling of light transport. The postdoc will primarily work on the experimental studies but will also have the opportunity to participate in computational and analytical
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interpersonal and communication skills. While not a must, a strong background in computational methods and/or statistical methods is a plus. Special Instructions Applicants should submit a formal application and
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, that means some museum and fieldwork!). Comparative analysis using advanced computational tools and wet lab techniques. Hands-on dissections of invertebrates for anatomical and physiological studies. Leading
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What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
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Mathematics / Computer Science Position Description Professors Le Xie and Na Li in the John A. Paulson School of Engineering and Applied Sciences (SEAS) at Harvard University seek a motivated postdoctoral
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place across the departments of Physics, Chemistry and Chemical Biology, Mathematics and the School of Engineering and Applied Sciences. Active research areas include quantum information and computer
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Requirements Strong computing and strong background/expertise in clustered data, survival data, causal inference or measurement error are desired. Strong written communications Additional Information: Per
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sophistication, including strong statistical skills and comfort with large-scale or complex data. Experience with computational text analysis, such as NLP methods, historical text processing, topic modeling