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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 10 days ago
statistical and econometric analysis, and produces tables and figures using statistical programming languages (R, Stata, or Python) Writes memos summarizing methods and results, and contributes to academic
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• Programming skills (e.g., Python, MATLAB, R) • Experience with AI/ML methods or power system modelling Conditional Offer The award of the PHAETHON PhD Studentship is strictly conditional upon the candidate’s
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: “The Biomedical Data Translator.” https://ncats.nih.gov/research/research-activities/translator These programmers will develop the following components to be incorporated into the ARAX (https://github.com/RTXteam
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infection and computational modeling . Preference will be given to candidates with research experience in the core areas of the group’s research; The candidate should have good programming skills (e.g. python
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of experience in Matlab or Python. Must be proficient in CAD software for rapid prototyping. Required Documents Resume To be considered for this position please visit our web site and apply on line at the
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for a Research Assistant to support an AI-enabled battery
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(i.e. Python, shell scripts, Java Script, Java, (PHP), Perl and PowerShell). Configuration formats such as YAML, JSON, and TOML Proficiency in Structured Query Language (SQL) Experience with Oracle, My
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Mathematics, or similar) Experience in energy modeling, optimization, or advanced algorithms Programming skills (Python, Matlab, or similar) Spanish and English required What We Offer High-impact national
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staff to carry out activities related to research lines or scientific-technical services Ref. Interna F1030-7812 PID2022-139551NB-I00 Call for selection of research asistants https://sede.urjc.es
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Vector, Vue.js 3, Node.js, Python, and JSON; Natural Language Processing (NLP) applied to collections; implementation of data pipelines using AI models, embeddings (RAG), and OCR; demonstrated knowledge in