97 computer-programmer-"University-of-Reading" Fellowship positions at Harvard University
Sort by
Refine Your Search
-
degree in economics, computer science, or another quantitative discipline (such as, but not limited to, physics, engineering, or mathematics). A strong foundation in programming (especially Python, Matlab
-
groups. The research and training plan of each fellowship must address important scientific questions within the scope of BIO and the specific guidelines in this fellowship program solicitation. Because
-
especially encourage candidates with proven experience in applying computational and experimental methods to social scientific questions – including aptitude in working with large-scale datasets and text
-
of our own evolutionary history, while domestication provides an additional window on brain-behavior evolution. The lab uses a variety of experimental and computational tools, such as structural and
-
of Organismic and Evolutionary Biology, which is a vibrant community of cross-disciplinary biological scientists at Harvard University. Basic Qualifications A Ph.D. degree in Bioinformatics, Computational Biology
-
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
-
for the analysis of problems in these fields, including data analysis, geometric signal processing and computational science, along with a deep commitment to working with, and alongside, experimentalists is a must
-
/scripting knowledge suitable for processing raw data for analysis (e.g., text manipulation); One or more computational environments for statistical analysis (e.g., MATLAB, Stata, R, or Python); Creating and
-
Bioinformatics, Computational Biology, or related areas; Hands-on experience with, or a strong interest in, bioinformatics programming, including Linux, scripting, and R; Expertise in data mining and cleaning
-
. Some areas of particular interest include: genetics, evolutionary biology, neurobiology, developmental biology, and stem cell biology. Our lab uses both experimental and computational approaches