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, biostatistics, data science, and related fields. Experience with human genomic data analysis. Professional programming skills, experience with high-performance computing, and cloud computing
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) be detail-oriented with programming experience in statistical software such as Stata, R, Matlab, or Python; (ii) have a strong quantitative background; (iii) be able to work independently to solve
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Training, Education & Mentorship This is intended to be a mentored academic research experience rather than simply a programming position. Trainees participate directly in research projects, lab meetings
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background in epidemiological and statistical methods, including coursework and/or research experience in evidence synthesis. 3. Programming experience using large datasets (e.g., R, Python). 4. Outstanding
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, geography, statistics, computer science, or related field Experience with remote sensing data analysis Strong skills in R programming and/or machine learning for spatial data Track record of
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models (LLMs), agents, or related areas solid programming and experimental skills excellent written and verbal communication skills the ability to work both independently and collaboratively The
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presentations and poster preparations. An emphasis will be placed on learning statistical programming using STATA software. Furthermore, we will provide education and feedback with manuscript preparation and
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. Strong programming and data analysis skills in Python and PyTorch; solid software engineering habits (git, testing, reproducibility). Demonstrated research independence with one or more first-author
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genetics Familiarity with large-scale human datasets (e.g., All of Us, UK Biobank, dbGaP) Experience in autoimmune, immunometabolic, neuroimmune, or cardiometabolic research Programming experience in
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background in computational modeling of behavioral data Experience with model fitting, parameter estimation, and model comparison Proficiency in at least one scientific programming language (e.g