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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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. • Proficiency in data acquisition systems, electronic instrumentation, and experimental control software. • Experience in experimental data processing and analysis using Python, MATLAB, or equivalent programming
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Engineer in Structural/Finite Element Analysis for Maritime Drone Operations
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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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/ Interview/ Test Good foundational coding skills (e.g, python) with a structured approach to coding. Essential Application/ Interview/ Test An interest in working with challenging real-world health care
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Python programming experience in machine learning and natural language processing ecosystems Essential Application/Interview Good expertise in basic statistics. Essential Application/Interview Familiarity
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more about logical zonotopes: paper link: https://lnkd.in/e-avQ-2B talk link: https://lnkd.in/eYGWFKmy You will conduct original research on logical–zonotope–based methods for model checking and digital
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modeling. The SCI Institute presents a highly challenging, collaborative work environment that can be deeply rewarding for the right individual. Further information is available at http://www.sci.utah.edu
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independently and as part of a collaborative research team. Preferred: Familiarity with relevant software packages and/or programming languages, such as Bruker TopSpin, Varian VnmrJ, Mestrelab Mnova, and Python
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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