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expertise in a supportive and innovative environment. In this role, you will lead the computational strand of the project, applying molecular simulations, data analysis, and machine learning to uncover how
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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to treatment, population health monitoring, workforce development and leadership, policy, and advocacy. Background The Robotics, Autonomy and Machine Intelligence (RAMI) Group led by Prof Nabil Aouf is dedicated
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control for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine
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proposals. Have a PhD in biostatistics or related subject with a numerate or computational component (including machine learning, data science, mathematics or a computational science), or a postgraduate
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programming language Experience with statistical inference or machine learning methods (e.g. ABC, Bayesian modelling) A proven publication record with at least one first author publication in a peer-reviewed
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mission is to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society. Singapore is the small city with a big dream. We are home
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unique combined system using an optimised AF scanning procedure that integrates Raman measurements to analyse lymph node biopsies within 10 minutes and machine learning algorithms to deliver quantitative