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) and strong general computer literacy, including the ability to quickly learn and use a range of research, administrative, and collaboration tools. Proven ability to work collaboratively within a team in
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, Health Sciences, Nursing, or a related field. Strong communication and computer skills (e.g. MS Office, Redcap, data management/analysis programs and other electronic communications). Experience working
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of the University may be required. Please review the position description for further information. About You You hold a doctoral qualification in Cognitive Neuroscience, Machine Learning, Computer Science or another
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disciplines including aerospace, combustion, design, fluid mechanics, materials, mechanical, mechatronic and robotics engineering. To learn more about the School click here . The Clean Combustion Group
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. Desirable: Proficiency in scientific programming (e.g. Python) and familiarity with data science and machine learning techniques. Experience with geochemical analytical techniques and working in a laboratory
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and research protocols in compliance-focused environments. Advanced computer skills with experience using Microsoft Word, Excel and PowerPoint; specific experience in working with a range of analytical
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Ability to work independently and collaboratively within an interdisciplinary team Excellent organisational, communication, and interpersonal skills Advanced computer skills, including Microsoft Office and
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed
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technologies will affect them. It is our anticipation that the work will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific