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contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and
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(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 LLMs. The candidate will apply
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. Teach courses related to chemistry, machine learning, or data-driven science. Supervise MSc and PhD students and contribute to curriculum development. Collaborate across departments and with external
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expertise in research and development in the following areas of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in
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techniques (FTIR, NIR, Raman, …) with machine learning/ chemometrics. Responsibilities of the Position The Postdoctoral researcher is intended to support the soil spectroscopy research activities and digital
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
dynamics, quantum mechanical simulations, and machine learning. Proficiency in programming languages and computational software’s. Strong motivation and passion for research in the field of sustainable
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machine-learning-driven multi-criteria decision analysis to rank and select optimal decarbonization pathways. Collaborate with industry and academic experts to ground-truth results. Dissemination Publish in
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-based observations, physical algorithms, and machine learning models. Participate in field data collection and validation to support model accuracy. Publish research findings in peer-reviewed journals and
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artificial intelligence (i.e. machine, deep and reinforcement learning…) to optimize efficiency, improve safety, reduce costs and promote sustainability. Collaborate with multidisciplinary teams to uncover a
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. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large