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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 month ago
stream chemistry data collected across a network of sites. The position will require downloading of data of field instruments and shared data repositories, and the development of code (R or Python based
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in MATLAB/Python/R are desirable but not required. The position is part of a well-funded research program and will provide the opportunity to produce high-impact publications and establish
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sufficient knowledge in the discipline and of research methods and techniques to work within established research programmes. Applicants will have coding skills in Python, PIP, JSON and HTML and will be
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Engineering. Solid knowledge of AI/ML, embedded systems, and IoT architecture. Programming skills in Python, ROS, TensorFlow, or MATLAB. Strong interest in applied AI and autonomous systems development
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consisting of Cornell and agency scientist. Specifically, the individual will: 1) Analyze acoustic data with existing software (Echoview, R, Python). 2) Collaborate with USGS scientists on field data
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, biostatistics, biomedical informatics or related fields OR a PhD degree in biology or related fields. Preferred Qualifications: A strong background in programming (e.g., Python or R or C++) is essential. Research
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., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer
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-postdocIBSoFACTo@emploi.beetween.com Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Skills/Qualifications Practical experience with bioinformatics tools (R, Python, etc.) is required
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at time of start) PhD or equivalent international degree. Preferred qualifications PhD in physics or astrophysics field. Strong programming skills (e.g., Python) for scientific computing and simulation
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solid experience in programming, particularly in Python and JavaScript. Significant experience in data science and machine learning will be highly valued. You like to work in a team while demonstrating