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announces an open competition for the position Ph.D. student - Machine learning-based tools for multiparametric enzyme optimisation Workplace: RECETOX, Faculty of Science, Masaryk University in Brno, Czech
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. You will become part of a dynamic, collaborative working environment with expertise in drilling engineering, geomechanics, machine learning, and energy systems. The project will integrate real‑time
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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for AI and Machine Learning included as well as industrial statistics), which will complement our current research portfolio (see https://stat.kaust.edu.sa) and have a research profile that can potentially
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Neutral Infrastructure (dfCO2), this role contributes to Program 4: Machine Learning for Carbon Performance (https://dfco2.org.au/program_4 ) that aims to advance the next‑generation AI methods to model
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Qualifications: Completed doctoral studies – PhD in bio-resource technology, practical implementation of Machine Learning, or a related field. Strong knowledge of Food security theory. Understanding of principles
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to apply Website https://www.academictransfer.com/en/jobs/359291/postdoc-in-machine-learning-and… Requirements Specific Requirements We will base our selection on the following components: a PhD degree in an
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Adaptive Learning in Brain-Robot Interactions School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year
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., computational learning theory, expressiveness of transformers and other models, xAI, formal methods) or equivalent; willingness to conduct research on artificial intelligence/machine learning, combined with
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Develop instrumentation and fixtures for the automation. Capabilities in advanced finite element or machine learning tools for process optimisation Disseminate the research outcomes into Journal