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, United States of America [map ] Subject Areas: Environmental Economics Natural Sciences Forestry Appl Deadline: none (posted 2025/08/28) Position Description: Apply Position Description Dr. Jeffrey R. Vincent, the Clarence
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(such as Seurat, Scanpy, etc.) Proficiency in R or Python for statistical computing and visualization Familiarity with dimensionality reduction techniques like tSNE, UMAP, PCA Experience with multicolor flow
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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
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or machine learning methods to tackle predictive questions. Proficiency in building and validating statistical methods and/or machine learning techniques in R or Python are also essential. Applicants
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collaboratively within a team Excellent written and verbal communication skills Proficiency in molecular bench skills and/or data analysis. Preferred to have familiarity with R, Python, or related scientific
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. Strong background in neuroimaging techniques (e.g., MRI, PET) and computational modeling. Proficiency in programming languages such as Python, MATLAB, or R. Experience with image processing tools and
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, quantitative psychology, rehabilitation sciences, or a similar field. Experience performing human subjects research Exceptional written and oral communication skills Preferred Qualifications Proficient in R
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. Lozada-Hildalgo, & P. Unwin. Nature. 2023, 620, 782–786. 2. Thousand-fold increase in O2 electroreduction rates with conductive MOFs. R. Mariano, O. Wahab, J. Rabinowitz, J. Oppenheim, T. Chen, P. R. Unwin
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Google Earth Engin, R, Python, and STAN (e.g., deep learning, Bayesian regression models, spatial analyses), and running analyses on a high-performance computing cluster. Demonstrated record of publishing
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Conservation Biology, or equivalent degree Preferred Education: Ph.D. in Ecology and Conservation Biology, Preferred Experience: Experience with R programming, statistical analysis of coastal datasets