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strong theoretical and technical background in vision research. Proficiency in programming (MATLAB or Python) and experience in human neuroscience research are required. Application Instructions
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
ability to program (e.g, python, R, and/or javascript). Must have at least some experience working with geospatial data. Preferred Qualifications, Competencies, and Experience Ability to develop impactful
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culture, flow cytometry, microscopy, and electrophysiology Experience with R or Python Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer. PD; SN Requisition ID
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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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programming in, for example, R or Python. Particularly valuable is a research background in ecology, biodiversity, systems biology, or related areas, as well as experience working with time-series data, dynamic
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, preferably in Python, Fortran, Matlab or R #experience in the environment of High Performance Computing (HPC) is desirable, but not mandatory #capability to work in a team but able to formulate and carry out
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skills in statistical software (e.g. R, Stata, Python) and working knowledge in SQL Excellent written and oral communication skills Strong record of distinguished scholarly achievement, including written
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of concepts and techniques from Quantum Information Science. - Experience with Python, Julia, Mathematica and quantum programming environments like Qiskit. Overtime Status Exempt: Not eligible for overtime
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. - Strong quantitative skills and experience coding in MATLAB or Python - Track record of publications and presentations. - Experience in mentorship and/or teaching. Preferred Qualifications • Demonstrated
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or fluency in python Excellent oral and written communication skills The ideal qualifications also include: Prior knowledge about land-atmosphere interactions, atmospheric dynamics, climate modeling, and/or