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Field
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experience in Python and/or C++ Strong mathematical and analytical skills Has experience working collaboratively within a multidisciplinary team. Excellent oral and written communication skills as demonstrated
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experience in Python and/or C++ Strong mathematical and analytical skills Has experience working collaboratively within a multidisciplinary team. Excellent oral and written communication skills as demonstrated
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(or a related field), is proficient in both mechanistic modeling and ML frameworks (e.g., TensorFlow, PyTorch), and has strong programming skills (Python/MATLAB/C++). Join us to tackle sustainability
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++ and Python are required. Experience with control and optimization of power generation systems (e.g., wind power) is desirable but not required. Some experience with real-time control hardware is
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, applied physics, computer science, or a related field. Required skills include an advanced command of Python. Mastery of a language in the C family is a plus. Some familiarity with programming of hybrid AI
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in Robotics, Computer Science, Aerospace Engineering, or related field Demonstrated expertise in SLAM, preferably aerial SLAM projects Strong programming skills in C++ and Python with ROS/ROS2
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in causal inference ● Minimum of 2 years’ experience in statistical software R, Python or equivalent Preferred Qualifications: ● Experience with development of R packages or other
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of clinical and multi-omic data to uncover microbiome–host relationships -Experience with Python/R and cloud computing required Ideal candidate: A computational biologist or bioinformatician with strong
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: C++, Python, Matlab, R. ● Building analytical pipelines that include image processing, image registration, auto-segmentation, feature extraction, pathomics, and radiomic analysis ● Proficiency
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, robustness, calibration, bias/fairness, and/or adversarial stress-testing. - Solid programming and ML/NLP engineering skills in Python and ideally modern deep-learning stacks (e.g., PyTorch/JAX, HuggingFace