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of the project (patents, communications, outreach). Conducting in vivo optical imaging experiments on healthy and patient volunteers; Developing image-analysis pipelines (Python, MATLAB) and modeling functional
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platforms such as Docker and Kubernetes, as well as traditional HPC server administration. Strong scripting skills in Bash and Python are essential for automating workflows and maintaining system efficiency
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holding a Bachelor’s degree in Oceanography, Geophysical Sciences, or related fields, who meet the following requirements may apply: a) Knowledge of python – information provided in the CV and/or motivation
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, computational biology, data science, computer science, electronics, biostatistics, applied mathematics, physics, biomedical engineering, or related fields). Basic programming skills, including MATLAB and Python
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assistants • Write scientific publications and present findings Required Qualifications • MA in computational social science, digital humanities, computer science, or related field • Python proficiency
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such as XBeach, SWASH, Watlab or CFD modeling is an asset Programming skills (Python, C++, MATLAB, or Fortran) are required Excellent analytical and problem-solving abilities along with a good team-spirit
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FieldEngineeringEducation LevelMaster Degree or equivalent Skills/Qualifications Conocimientos de sistemas LLM y GenAI. Evaluación de modelos. Programación en Python. Specific Requirements Programación en Python. Diseño y
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experiments to understand and improve tool performance, and – most importantly – by summarizing findings in white papers and application notes. A full job description can be found here: https://mitnano.mit.edu
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solutions. For more information about DHS visit: https://www.dhs.gov/mission. Project The DA-TC is seeking candidates who have the academic background to engage in the following projects. Projects will be
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly