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-tuning using modern frameworks. Software Engineering Excellence: Demonstrates expert-level Python skills and a strong commitment to Software Engineering best practices, writing code that is clean, modular
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, scripts, or lightweight applications using Python, R, or JavaScript Manage research code, data pipelines, and documentation Support the preparation of academic manuscripts, technical reports, and policy
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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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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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scientific computing environment (e.g. Python, MATLAB, Modelica); experience with geothermal or reservoir modelling tools is an advantage. We regret to inform that only shortlisted candidates will be notified
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(RAG), and fine-tuning using modern frameworks. Software Engineering Excellence: Demonstrates expert-level Python skills and a strong commitment to Software Engineering best practices, writing code
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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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Research Associate (Artificial Intelligence/Computer Science/Optimization/Computational Linguistics)
solutions Requirements: Master’s degree in Artificial Intelligence, Computer Science, Optimization, Computational Linguistics, or a related field. Strong foundations in multi-agent systems, NLP and python
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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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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP