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candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically
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predictive maintenance in chemical plants. Key Responsibilities: Create and implement hybrid AI models that merge machine learning techniques with mechanistic frameworks (like physics-informed neural networks
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
, including molecular dynamics, quantum mechanical simulations, and machine learning. Proficiency in programming languages and computational software’s. Strong motivation and passion for research in the field
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, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases
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Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming tools such as R packages, Phyton, and other programming languages Publications in the field Excellent
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modeling, satellite remote sensing, or machine learning Programming skills (Python or R) Strong publication record
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models that merge machine learning techniques with mechanistic frameworks (like physics-informed neural networks and grey-box modeling) to enable predictive simulations of chemical and biochemical
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industrial conditions. Keywords: Artificial intelligence, autonomy, digital twin, edge computing, UAV systems. Objectives: Support the development of AI and machine learning algorithms for autonomous
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
Computational Chemistry, Materials Science, or a related field. Strong background in computational chemistry techniques, including molecular dynamics, quantum mechanical simulations, and machine learning
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industrial applications. Contribute to the development of scalable and interpretable AI tools for real-world deployment. Qualifications: A PhD in Computer Science, Machine Learning, NLP, or a related field