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language proficiency (IELTS overall minimum score of 6.5). Also, the candidate is expected to: Have excellent analytical, reporting and communication skills Be self-motivated, independent and team player Be genuine
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language. Motivation, flexibility, sense of responsibility, ability to listen and compromise, autonomy, and problem-solving skills. Ability to work with a small cutting edge commercial/academic technology
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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” highly flexible components and ensure their energy harvesting capabilities. This project will contribute to ambitious plans for SBSP as a vital part of the future Net Zero landscape. Recent advances in
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environment for all PGRs creating a strong sense of community across research disciplines. Community and research culture is important to our PGRs and the FoE support this by working closely with our
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Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past
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life-cycle analysis, GasTurb/PyCycle/NPSS, and CoCip is preferred Excellent written and verbal communication skills[AR1] is preferred. To apply, please contact Dr Eastwood - david.eastwood
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The student will benefit from working alongside a multidisciplinary team of engineers, mathematicians, and physicists at the University of Manchester as well as a wide collaboration network within the UK and
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student community and maintain a culture where everyone can work and study together harmoniously with dignity and respect. This is reflected in our University values of ambition, impact, respect and
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outcomes: Exploring associations between loneliness and depression symptoms over time using network approaches Supervisors: Dr Ann-Marie Creaven (ann-marie.creaven@ul.ie ) ; Dr Aoife Whiston (aoife.whiston