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technologies (e.g., spatial transcriptomics, CODEX, Akoya PhenoCycler). Proficiency in single-cell RNA sequencing, high-dimensional data analysis, bioinformatics tools, and programming languages (R, Python
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in software development skills in programming languages such as R and Python. Knowledge, Skills and Abilities Skill in managing one’s own time and the time of others. Ability to analyze, organize and
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++, and Python. Preferred Qualifications Prior research experience in computer systems and distributed computing is preferred. However, strong research experience in developing/applying machine learning
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or Python. Lastly, candidates should have experience performing human subjects experiments. Application Material: Curriculum Vitae with pointers to your research/expertise-related online profiles (e.g
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, policymakers, and advocates. Programming skills are essential (we mostly work in Python, though other languages are welcome), as is a strong grasp of statistics and an eagerness to learn more. Recommended
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circuit using one or more of the software listed (Cadence; Fluent use of LT-Spice, Verilog-A, Python, ADS, ICCAP, etc.) Know how to perform circuit analysis and characterization Notice of Non-Discrimination
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Boltzmann method (LBM), discrete Boltzmann method (DBM), and other kinetic models. Solid knowledge of fluid dynamics and heat transfer. Proficiency in programming languages such as C/C++, Fortran, Python
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positions in the professional ranks. Preferred Qualifications Strong background in mathematical modeling, optimization, and simulation techniques. Proficiency in relevant software tools (e.g., MATLAB, Python
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Science, Statistics, Mathematics, Computer Science, or a closely related field. Demonstrated expertise working with multivariate time-series and spatiotemporal datasets. Advanced proficiency in Python
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foundation and programming skills in languages such as Python, Java, Julia, MATLAB, R, and/or C++. Expertise in one or more of the following: machine learning, deep learning, HPC, Docker/Singularity