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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 12 hours ago
or related areas; demonstrated publications; strong computational skills (e.g., Python, MATLAB); and experience analyzing large datasets and communicating results effectively. PREFERRED : Experience with
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requirements include: Candidate should minimally hold a master’s degree in maritime transport, marine technology, computer science, or a related field. Excellent programming skills, such as Python, Matlab, C
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statistical and geospatial analyses (e.g., using ArcGIS, SPSS, Stata, Python, R). Conduct cross-city comparative research Map and analyse the geographical distribution of eviction patterns within and across
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part of change Conception of novel stochastic source coding techniques based on channel simulation Development of numerical Python code for evaluation Optimization and refinement of these techniques in
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methodology. Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses. Developing benchmarks and working together with staff
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platforms and our local CPU and GPU clusters; implementing Python tools for automating CSP/DFT calculations; - Participation in the scientific activities of the Applied Quantum Chemistry group (IC2MP) and the
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geospatial data processing and python programming. Candidates should also have knowledge of optical, lidar, and ground penetrating radar sensing systems and understanding of pavement structures and condition
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also include trouble shooting capabilities. Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance
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Helmholtz-Zentrum Berlin für Materialien und Energie | Jena, Th ringen | Germany | about 15 hours ago
/automated chemistry Good programming skills, e.g., Python Very good written and spoken English skills You demonstrate a high level of commitment, initiative, problem-solving skills, and a willingness to
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methods of soil characterization, monitoring and management, Organization of field campaigns, data collection and lab work, Spectral data analysis, data processing, and model development, ‘R’, Python