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the University of Birmingham. We are looking for a highly talented and dedicated PhD student with a 1st class or upper 2:1 degree in the field of transport studies, civil engineering, mathematics, social science
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project “Blockchain incentives: consensus and fairness”. The project’s aim is to provide a systematic analysis of blockchain protocols with respect to the strategic behaviour of the stakeholders and related
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chemistry, biophysical analysis via optical spectroscopy as well as the detection of nucleic acid in homogenous solution and in situ. The project also involves fluorescence microscopy and flow cytometry and
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) design and analysis skills. Provide evidence of strong oral and written communication skills. Meet RMIT University's entry requirements for the Higher Degree by Research programs. The scholarship is open
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to have a background in engineering and/or an affinity for mathematical modelling and sustainability assessment methods such as life cycle assessment. Affinity with pharmaceutical manufacturing or chemical
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of Information Technology website . The project will be led by Professor Carolina Wählby , within the Image Analysis unit of the department’s Vi3 division, working alongside researchers developing numerical and
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. To meet the general entry requirements for doctoral studies, you must: Hold a Master’s degree in computer science, image analysis and machine learning, engineering, data sciences, applied mathematics
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technology, or applied mathematics, with a specialization in energy systems analysis, or energy economics. Strong written and verbal communication skills in English. The following experience will strengthen
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Science, Statistics, Applied Mathematics, or a related field. • Strong background in convex analysis, statistical machine learning (reinforcement learning, LLM and generative modeling), stochastic modeling and
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) biological knowledge about GRNs from bioinformatics and system biology, (b) graph theory and topological data analysis for network modeling from mathematics, and (c) robust machine learning (ML) and GenAI from