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(particularly under extreme conditions), and/or the use of machine learning for solid mechanics/stress analysis problems are encouraged to apply. The job description presented here is deliberately broad due
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strong analytical skills and desirably some computer modelling experience, and an ability to work in a multidisciplinary team and engage confidently with partners. You will have a track record of
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effects and their coupled interactions. In effect, this a complex problem that needs the application for AI / machine learning to enable guided, efficient and effective optimization of the CHIPLET
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; ongoing learning and development opportunities to grow your career; an inclusive and supportive culture and environment to work in, both online and on campus. Who are we? Deakin is a cutting-edge public
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independent thinkers, curious and intrinsically motivated, with a passion for basic research. Postdoctoral fellows in the lab bring or learn diverse tools, including: Protein expression and purification
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Responsibilities: To independently undertake research in data privacy, machine learning, and applied cryptography. To produce research papers and reports as required by the funding body or for dissemination
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on innovative design for legal and regulatory systems for AI and other complex global technologies; computational models of human normative systems; and working with machine learning researchers to build ML
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science and artificial intelligence concepts and tools to solve complex problems. Candidates will also be developing machine learning techniques and applying them at scale to specific projects with regular
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transmitted to the larger organization. Qualifications § A PhD in Electrical and Computer Engineering, Applied Physics, or a related field § >3 years experience with Lumerical and Comsol electromagnetic
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, brain science, and neuroscience); data science and machine learning; modeling, analysis, simulation and prediction for biological, engineering, physical and quantum systems; probability theory and