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preferred candidate will have experience teaching data wrangling, programming in Python and base R, and industry experience in data analytics or data science. The role will cover the full range of duties
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for gene regulatory networks, single-cell multi-omics integration, spatial omics, and variant effect mapping in complex disease. Strong method/tool dev experience required (Python/R, ML/stats
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programming language (Python or similar) and experience with UNIX/LINUX. (Required) Education, Licenses, Certifications & Personal Affiliations Master's Degree in quantitative methods, statistics or a related
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Singapore English Mental Lexicon project is available at https://langcomplab.github.io/singlish.html Information about the department is available at: https://fass.nus.edu.sg/psy/ Qualifications Candidates
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micro data on firms, banks, investors, currencies, trade and financial asset transactions is welcome. Familiarity with Python, Stata, R, MATLAB, SQL is preferred. Candidates should address how they would
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communication skills in written and spoken English. Proficiency in programming with high-level languages like Python. The following will strengthen your application: Familiarity with open quantum systems
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/ ROS 2 for real-robot software integration. Proficiency in Python and C++, with good software engineering practices (version control, testing, maintainable code). Familiarity with robotics simulation
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statistical and machine learning methods, particularly for high-dimensional or longitudinal data. Demonstrable experience in research software development using R or Python and a track record of contributing
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large environmental and ecological data sets, incl. empirical, remote-sensing and simulated model data knowledge in programming languages (UNIX, C, or similar) and script-based programming (R, Python
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Python, PyTorch, and Linux/command line Familiarity with LLM in-context learning and prompt engineering Basic understanding of modern LLM models, ecosystems, and pipelines, including retrieval-augmented