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Field
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possess strong quantitative skills (e.g. Matlab, C++, Python). The term of this appointment is one year with the possibility of renewal contingent upon satisfactory performance and continued funding
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spatial transcriptomic data using R or Python; interprets findings in the context of transplant immunobiology. Establishes new research protocols and procedures: Develops and optimizes protocols
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learning methodologies. The underlying data are complex and will require sophisticated data management and integration skills. A candidate should have proficiency with GIS software and Python, strong written
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proficiency in languages such as R and Python. Experience in GIS, remote sensing, and processing projected climate data. Proven ability to manage multiple tasks effectively, work collaboratively in team
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. Knowledge of programming languages (e.g., C, C++, Python, R, Matlab) is preferred. Primary Responsibilities: The successful candidate(s) will be expected to carry out research under minimal supervision
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documents. A well-qualified candidate will also possess: Advanced scientific programming skills using a variety of computer languages, including but not limited to Python, C, C++, and Fortran. 5 years
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programming language (preferable: MATLAB or Python) Experience with one or several of the listed human neuroscience techniques. Ability to work and learn independently and perform research with a high level of
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, including fitting and manipulation of large array-type data sets (using Python, Matlab or equivalent) Ability to communicate well, and work within a collaborative team environment Preferred Knowledge, Skills
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. Experience with large-scale omics data analysis and programming (R or Python). Proven track record of high-quality publications. Experience with molecular biology techniques (e.g., cell culture, CRISPR, NGS
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(Python, MATLAB) for processing and analyzing large or multimodal datasets (e.g., neural activity and behavior). Experience working with quantitative behavioral or electrophysiological data collection