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-equilibrium conditions. The project is a UKRI/NSF collaboration with Virginia Tech, and the use of direct numerical simulation, modelling and analysis will be complemented with experimental data from
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involves qualitative data collection with people living with brain tumours, their communication partners, speech and language therapists (SLTs), and other healthcare professionals. Stage 2 uses co-design
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees
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interpretation of platform data, stakeholder feedback, and project outcomes; maintain records and databases; and draft progress reports, technical reports, and academic publications. Contribute to the design
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the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative
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the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative
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measurement in construction. The skills, qualifications and experience required to perform the role are: Hold (or be close to obtaining) a PhD in Computer Science, Civil Engineering, Data Science, Information
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effort between School of Engineering and School of Chemical Engineering at Aalto University supported by our industrial partners. The PhD student to be jointly supervised by two supervisors; Prof. Hamid
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systems theory Excellent analytical and problem-solving skills Desirable criteria Advanced programming and data analysis skills Computational neuroscience background Behavioral data analysis skills Strong
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, alongside complex drug screening, efficacy and clinical phenotype information. Using these datasets, you will undertake comprehensive strategies aimed at the characterisation and therapeutic targeting