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Field
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highly skilled Postdoctoral Fellow with a proven dual‑mode research profile capable of independently performing laboratory experiments and coding predictive AI models in Python to forecast biomaterial
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Proficiency in programming languages such as C, C++ and Python We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU
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. Additional Qualifications: • Theory: Expertise in quantum optics, quantum information science, or quantum field theory. • Simulation: Proficiency in MATLAB or Python for simulation/modeling and data analysis
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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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, or unsupervised learning methods. Proficiency in Python and familiarity with scientific computing libraries such as PyTorch, TensorFlow, Pandas, NumPy, and related ML frameworks. Experience with large datasets
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, Python, or equivalent will be an advantage. Prior experience in laboratory testing, data analysis, or industry-related engineering projects will be an advantage. Key Competencies Ability to build and
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Python or other equivalent programming languages. Strong foundation in data analytics and data-driven modelling. Able to build and maintain strong working relationships with people within and external
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University and the broader NYC cognitive science community. Responsibilities Include: Research & Analysis Develop and maintain Python-based pipelines for large-scale data processing (images/video, text
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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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signal processing skills (e.g., using Python and/or MATLAB). Ability to work effectively in an interdisciplinary team and communicate clearly across disciplines. Experience handling large datasets and