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(e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference, causal
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of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in design and very good programming skills (Python, Pytorch
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of future research proposals. Skills, Experience & Qualifications Needed PhD in an appropriate subject area (awarded or submitted). Proficiency in Python for scientific computing, including basic scientific
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
Experience Applicants must have experience writing and modifying scientific code, performing data analysis or simulation workflows, and proficiency in at least one programming language such as Python, C, C
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, tissue sections, RNA/DNA, tabular data) for predictive modelling using software such as Python Documented experience of neural networks, image processing, deep learning algorithms, and data visualization
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Education, STEM Education, Statistics, or a closely related field. Experience conducting quantitative analysis using statistical software such as R or Python. Experience conducting educational, social science
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Python. • Knowledge of the Pytorch library for neural network development would be appreciated. Interpersonal skills: • Candidates must be able to work as part of a team with the various project
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analysis Experience using R or Python Pay and Benefits Pay Range: $62,232 - $75,564; depending on education/qualifications/experience and following the NIH stipend level Please visit the Benefits
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. Basic proficiency in using Python and/or command line interface (CLI). Basic understanding of raytracing and optical design. Experience with SharePoint, SolidWorks PDM vault, GitHub. Required Documents
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algorithms (Python, Matlab, or equivalent). Experience with deep neural networks, particularly for the analysis of spectral or imaging data, will be highly appreciated. Knowledge of light propagation in