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applications Familiarity with engineering software such as ABAQUS, ETABS, MATLAB, Python, or equivalent will be an advantage. Prior experience in laboratory testing, data analysis, or industry-related
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, or machine learning. Proficient in programming languages such as Python, C++, and MATLAB. Strong publication record in relevant research areas. Excellent communication and teamwork skills. Modes
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* Doctoral degree in Kinesiology, Psychology, Computer Science, Biomechanical Engineering, or a related field. A high degree of proficiency using R, Python, and/or Matlab to process and analyze time-series
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biological mechanisms utilizing U-M Core Facility resources. Experience in Python or R programming is highly preferred. Mission Alignment: Candidates must demonstrate a clear interest in ecology and species
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or TensorFlow. Advanced programming and high-performance computing skills, including proficiency in Python and/or C/C++, experience with GPU acceleration, and the ability to develop, test, and maintain research
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master exam before 30.06.2026. It is a condition of employment that the master's degree has been awarded. Good programming skills (Python, Matlab or Julia) are a requirement. A solid background in
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, or a related discipline. Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage
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software such as STATA, R, or Python. Potential to publish articles in high quality international academic journals. Ability to work in teams as well as independently. Written and spoken proficiency in
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 6 days ago
. Preference will be given to candidates with aptitude for working in disaster risk management environments supported with GIS and Machine Learning, basic programming skills (e.g., Python, R, or similar
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such as R or Python Manage the full biomarker panning workflow, including strategic planning, operation oversight, biomolecular sample characterisation using UHPLC glycan analysis, mass spectrometry and