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commonly used in genetics and molecular epidemiology. Expertise in R, Python, bash is required. Strong communication (oral and written) and interpersonal skills, and experience working in a large research
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pursuing a bachelor's degree in the one of the relevant fields anticipated to be received by May 31, 2027. Preferred skills: Experience with fire management, landscape ecology, programming (e.g., R or Python
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field. Minimum of 2 years’ experience in cell culture, in vivo work, confocal microscopy or computational analysis of RNAseq in R/Python. Preferred Qualifications: Experience with primary cell culture
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scientific software development. Proficiency in C/C++ and Python, with experience in HPC environments (e.g., MPI/OpenMP; GPU experience a plus). Record of peer-reviewed publications appropriate to career stage
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completed all requirements for the Ph.D. by the start date) • Strong training in causal inference and empirical research methods • Proficiency in Stata, R, Python, or similar Preferred
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or machine learning. Excellent programming skills in Python and deep learning frameworks A collaborative mindset and interest in socially impactful research. Experience with sign language data, multimodal
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sequencing data analysis, variant interpretation, and bioinformatics workflows used in research and diagnostic settings. Strong programming skills (e.g., R, Python, Perl, C/C++, Bash) and confidence working
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compositionality with large language models. * Strong Python and ML ecosystem skills (e.g., PyTorch, scikit-learn, etc.). * Facility with C/C++/Rust or other systems-level programming languages * Skilled in writing
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) data sets in R or Python as well as GIS software such as QGIS or ArcGIS Pro. Knowledge of US forest ecosystems and background in analyzing forest structure, stand dynamics, biodiversity, and/or other
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of algorithm-hardware co-design, especially for robotics or edge AI deployment. Strong programming skills in C, C++, and Python, with experience in deep learning frameworks such as PyTorch or TensorFlow