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, performance analysis and optimization. Demonstrated capability to conduct innovative research. Proficiency in basics of programming languages such as C, C++ and Python. Ability to initiate collaboration
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characterization (SEM, TEM, XPS, FTIR, etc.) Programming skills (Python, MATLAB, or similar) Exposure to machine learning methods (e.g., Bayesian optimization, active learning) is an advantage Understanding
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Prior experience with polymers, carbon nanotubes or sensors. Proficiency in data analysis tools (Excel, Origin, Python, etc) Familiarity with spectroscopic techniques (fluorescence, Raman, UV-Vis
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models, and foundation models Strong programming skills in Python and deep learning frameworks such as PyTorch Experience with large-scale experiments, model optimization, and performance analysis
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to diverse academic and industrial audiences. Proficiency in Python and deep learning frameworks such as PyTorch. Experience with Linux environments and GPU cluster management is essential. Competent in
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students and working effectively in a team-based research environment Proficiency in common computational chemistry software and coding techniques e.g. Gaussian/Amber/Schrödinger/python/bash For more
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with neuroimaging software (e.g., SPM, AFNI, FSL). Familiar with coding (e.g., in R, MATLAB, Python). Experience with research project management. Experience with supervising research staff and students
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physics, with experience in thin-film deposition, device fabrication, and electrical transport measurements Familiarity with the theory of magnetism Proficiency in MATLAB/Python and LabVIEW for data
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governance. Proficiency in SPSS, Python, R, or MATLAB for data analysis and visualisation. Experience in designing and evaluating exercise/prehabilitation programmes. Track record of publications and ability
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with retrieval-augmented generation (RAG) frameworks is an advantage. Strong programming skills (e.g., Python, R, or similar). Interested applicants are invited to submit a full CV and cover letter in