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Field
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parameters implement and document analysis workflows in Python (automation, visualization of stress maps, reproducible pipelines) What you bring to the table enrolled as a student in the field of
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scientific ideas. Previous experience with statistical analysis, programming (e.g., R or Python), machine learning, or genomic data analysis is an advantage but is not required. We welcome applicants who
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programming skills and experience, especially in Python, R or SQL; and ability to work independently to solve problems. Candidates must have authorization to work in the US for the duration of the appointment
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tools in R, Python, or MATLAB. Demonstrated desire to learn new neuroscience and stem cell engineering techniques. Excellent organizational, record-keeping, and interpersonal communication skills
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neuroscience or a related field of study Extensive experience with programming (Python or Matlab) Passionate about human neuroanatomy and cognitive neuroscience Highly advanced and flexible command of
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
and Experience: Methods and techniques of observational astronomy. Computer programming in languages such as Python. Oral and written communication skills, including scientific and technical writing
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radio-frequency experiments, superconductivity, or layered materials, as well as Python programming (or similar) is a plus. Most importantly, an applicant should be driven by curiosity and should be
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arrays. • Familiarity with computational biology pipelines (e.g., handling transcriptomic or scRNA-seq datasets using R or Python). Special Instructions to Applicants: In order to be considered, you must
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University of Geneva | 2 months ago
/Astrophysics/Physics or in a related field by the start of the position, with some experience in research and Python. A background in extragalactic studies (especially JWST or VLT spectroscopy) is an asset. The
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candidates with a Master's degree in (computational) chemistry, physics, or materials science who are curious about applied machine learning in the natural sciences. Prior machine learning or Python