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, Python, GitHub, fieldwork, laboratory workflows, or grant/manuscript development. Experience with R, Git/GitHub, phylogenomic or population genomic workflows, GIS/spatial analysis, herbarium curation
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independently and as part of a collaborative research team. Preferred: Familiarity with relevant software packages and/or programming languages, such as Bruker TopSpin, Varian VnmrJ, Mestrelab Mnova, and Python
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, preprints, or thesis work. ● Proficiency in a scientific computing language (Python, MATLAB, Mathematica, Julia, R or C/C++). Preferred Qualifications: ● Prior experience with the Chemical Master
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proficiency in finite-element implementation through at least one of FEniCS/FEniCSx or Abaqus user subroutines (UEL/UMAT) in Fortran, together with scientific programming in Python. Knowledge, Skills
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, or academic projects • Experience in writing research code in collaborative settings using languages such as R and Python • Ability to work effectively as part of a multi-disciplinary research team • Strong
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, Photoshop), R, and/or Python. • Ability to work effectively with faculty, staff, and students from a variety of diverse backgrounds. • Ability to contribute to institutional diversity, equity, and inclusion
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, or other real-world data sources. Proficiency in R, SAS, Python, Stata, or similar analytic software. Demonstrated experience contributing to manuscripts, scientific abstracts, reports, or grant applications
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generator code, C++, Python. Excellent verbal and written skills. Presentation skills. Analytical skills. Attention to detail. Salary: Compensation will be commensurate based on the selected candidate's
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relevant programming language (e.g., R or Python). Strong written and oral communication skills. Experience managing multiple projects at once. Willingness to learn new technical skills and gain knowledge in
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Classification Title: Post-Doctoral Associate in unsupervised and generative ML for chemistry Classification Minimum Requirements: PhD in Chemistry or related area Strong coding (Python) and