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for gene regulatory networks, single-cell multi-omics integration, spatial omics, and variant effect mapping in complex disease. Strong method/tool dev experience required (Python/R, ML/stats
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Practical experience with vector network analyzers and on‑PCB LRM/TRL calibration/de‑embedding. Proven experience in behavioural modelling and DPD (MATLAB/Python) Desirable Criteria Knowledge, Skills
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/ML/CV venues Proficiency in Python and deep learning frameworks Experience in machine learning, computer vision, or NLP Strong communication and collaboration skills Our commitment to inclusion and
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/ ROS 2 for real-robot software integration. Proficiency in Python and C++, with good software engineering practices (version control, testing, maintainable code). Familiarity with robotics simulation
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
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communication skills in written and spoken English. Proficiency in programming with high-level languages like Python. The following will strengthen your application: Familiarity with open quantum systems
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research. We are seeking a highly motivated Research Fellow to join our dynamic team
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in complementary methods such as ICP-MS, XRD, XPS, SEM, TEM, EDX Scripting in Matlab, Python or equivalent languages for data analysis Strong publication record in peer-reviewed journals What you will
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the use of databases or knowledge in data processing and statistical metrics*; 2. Proficiency in English*; 3. Knowledge of Python, MATLAB or R programming languages*; * mandatory requirement Work plan: The
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Python, PyTorch, and Linux/command line Familiarity with LLM in-context learning and prompt engineering Basic understanding of modern LLM models, ecosystems, and pipelines, including retrieval-augmented