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. • Strong proficiency in Python, FastAPI, and PostgreSQL. • Hands-on experience with LLMs, vector databases (e.g., Pinecone), and NLP tools. • Familiarity with clinical trial data structures, academic
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Future robots must perceive, predict, communicate, and decide reliably in complex, human–robot shared environments. The Mobile Robotics (https://www.aalto.fi/en/department-of-electrical-engineering
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treatment resistance in ovarian cancer. Vähärautio lab (https://vaharautiolab.org/) at the Medical Faculty, University of Helsinki, is seeking a bioinformatician or a computer scientist with strong
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instrumentation. Experience with Python, model/API integration, retrieval-augmented generation, tool-using agents, scientific databases, and automated experimental platforms is highly desirable. The candidate is
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: Computer Science or Computer Engineering; • PhD: Computer Science or related fields within the last 7 years; • Knowledge of: Python, DL, CV, Transformers, LLMs, NLP; • Relevant scientific publications; • English
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materials characterization (e.g., SEM, XRD, FTIR, mechanical testing). Proficiency in data analysis tools (Python, MATLAB, JMP) and technical documentation. Strong analytical skills and attention to detail
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, Electrical and Electronics Engineering, Earth Sciences, Remote Sensing, and Artificial Intelligence are also well-suited. (More details on PhD requirements can be found at: https://nusgs.nus.edu.sg
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 10 days ago
languages like Python. The group currently leads development of spaceflight readout electronics for the Probe Far-Infrared Mission for Astrophysics (PRIMA) and the balloon-borne EXperiment for Cryogenic Large
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in Python and working with machine-learning frameworks and libraries, e.g., PyTorch, TensorFlow, Hugging Face Strong conceptual understanding of clinical and biomedical research, data standards, and
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(interactive phylogenetic trees, Sankey diagrams). Report generation and statistical analysis • Statistical analysis of viral abundances (Wilcoxon, ANOVA), regression models (R, Python: statsmodels, scikit-learn