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, using R or Python; experience with these datasets is helpful but not required Preparing statistical reports and presentations Presenting findings at regional or national scientific meetings Mentoring
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
to analyze high dimensional medical imaging data* Make it easy to get high quality, automated, results without expert intervention. Build scalable products and reusable libraries in Python, Scala, and/or C
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, R’ or Python programming, Co-supervise PhD and undergraduate students. Be willing to be involved in other research activities different than spectroscopy, such as soil phosphorus, agronomy
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of cold atoms in a resonant cavity, helping to interpret current experiments of Esslinger and Domokos groups as well as providing theoretical predictions and propositions. Good computer skills (julia/python
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and work cooperatively with others. Preferred Special Knowledge, Abilities and Skills: - Experience in programming languages such as Python, R, Stata, SAS, SPSS. - Strong command of large dataset
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) - Very good acoustic analysis skills - Good knowledge of speech production models - Very good statistical analysis skills - Good academic English skills (C1) - Very good programming skills (Matlab, Python
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using Python and Fortran programming language. Responsibilities: Conduct a literature review and gap analysis of existing models on methane and nitrogen gas production, livestock enteric fermentation, and
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machine learning. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software
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of the GRISLI model Code programming in Python and Fortran Write scientific articles - good level of English required Analysis of a large set of GRISLI simulations and sensitivity study Presentation of results
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responsibilities for this role include: Initiating, planning, and overseeing research projects Leading the analysis of complex multiomics data, including single-cell and spatial omics, using R or Python; experience