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–driven coagulant dosing). Desired qualifications: ● PhD in Environmental Engineering, Electrical/Computer Engineering, Applied Physics, or a related field. ● Strong programming skills (Arduino
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: Writing sample Sample of R or Stata computer code Regional Campus Rutgers Biomedical and Health Sciences (RBHS) Home Location Campus Piscataway (RBHS) City Piscataway State NJ Location Details Pre
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/modeling, at the Electrical and Computer Engineering Department, and in collaboration with the Applied Mathematics Department, Santa Clara University. This is an in-person position at Santa Clara University
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duties. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word, Excel, and PowerPoint. Must have the ability to work collaboratively and
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primarily office-based and involves computer and analytical work in a standard office or research environment. Must adhere to all Brookhaven National Laboratory (BNL) environmental, health, and safety
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. Qualification requirements: Applicants must hold a degree equivalent to a Norwegian doctoral degree in geosciences, environmental sciences, computer/data science, physics, applied mathematics, or other relevant
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scientists, and domain scientists conducting basic and applied research in support of ORNL’s mission. Specific responsibilities include: Participation in the development and analysis of new computational
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implement new computational and statistical methods. Create, test, and use relevant computer code (R, Python, SQL or equivalent). Maintain, modify, and execute analytic machinery that results. Draft
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scientists, and domain scientists conducting basic and applied research in support of ORNL’s mission. Specific responsibilities include: Participation in the development and analysis of new computational
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 3 months ago
-Assisted Intervention, Oct 2024, Marrakech, Morocco. pp.1-10, * B Lodé et al. Evaluation of an Automatic Segmentation Model as an Aid to Detect Multiple sclerosis Spinal Cord Lesions. European radiology 2025