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Bayesian statistics, stochastic modeling, and optimization under uncertainty • Proficiency in Python programming • Strong interest in applied and transferable research • Knowledge of industrial simulation
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machine learning and statistics; experience with Gaussian process regression and/or probabilistic regression. Experience with normative modelling is an advantage. Proficiency in Python (and ideally C/C
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systems Conduct data collection, cleaning, quality assurance, and validation activities Develop models to analyze costs and performance of wastewater technologies in Python or similar format. Participate in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
, automated, results without expert intervention. Build scalable products and reusable libraries in Python, Scala, and/or C++, taking advantage of Spark, Hadoop, and other tool stacks as appropriate
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Qualifications: Ph.D. (completed within the past 0-5 years) in computer science, electrical engineering, applied mathematics, or a related field. Strong proficiency in Python, with additional experience in C, C
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. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software packages for data
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molecular spectroscopy and nonlinear optics, and is a must for recruitement. Additional qualifications such as training and supervision of master students, and proficiency in Python and/or Matlab are valuable
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, hydro-acoustics, data science, geodynamics, geophysics, statistics, Bayesian inference ⁃ Experience with statistical analyses and machine learning techniques ⁃ Programming in C / python / Julia
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and active‑heating rigs; Strong programming skills (Python/Matlab and/or FEM packages); Publication record appropriate to career stage; Excellent teamwork, project‑management and communication skills
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candidate (m/f/d) has expertise in population genetics, computational data analysis and microbial evolution, with a solid understanding of quantitative statistics and programming (python, R, matlab etc