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remaining. • Self-motivated and able to work independently and collaboratively • Strong communication skills • Proficiency in R, Python, or MATLAB • Familiarity with spatiotemporal analytical approaches and
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
Python, Julia etc. with knowledge or keen interest to develop and meaningfully incorporate advanced AI/ML algorithms to advance their research. Experience creating and/or working with computational
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, Freesurfer, UNIX/LINUX computational environments and/or programming skills (MATLAB, R, C++; JAVA, Python) is desirable, but not required. Applicants who have experience in the study of children (especially
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Expertise in machine learning, including building and deploying prediction models Strong data science coding skills in programs and languages such as Python, R, Stata, and SQL Experience with research in
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modeling, inference, and compressed sensing. Experience deriving biological insights from large datasets, including mass-spectrometry and DNA-sequencing datasets. Proficiency in Python or another general
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) software (e.g., COMSOL, ANSYS, or custom FEM codes) Proficiency in one or more programming languages (e.g., MATLAB, Python, C++, Julia). Strong written and oral communication skills Ability to work
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Python * Experience with version control systems like Git * Experience working as part of large-scale research, scientific, medical, or academic projects * Experience working in, or in support of, public
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not have exceeded two years previous work at the postdoctoral level at start of appointment. Coding experience in a scientific computing language is desirable (e.g., Python, MATLAB, R, IDL, Fortran, etc
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primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science, and
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experience with large-scale human datasets, machine learning, statistical genetics, causal inference, multi-omics, cardiovascular imaging, programming in Python or R, and scientific writing. Prior experience