21 evolutionary-computation Fellowship research jobs at Monash University in Australia
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Research Fellow - Environmental Informatics Hub Job No.: 680160 Location: Clayton campus Employment Type: Full-time Duration: 2 year fixed-term appointment (with the possibility of an additional 2
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for Health Economics is seeking a Level A Research Fellow to play a key role in an ongoing research program examining the effectiveness and cost-effectiveness of behavioural interventions, with a particular
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. We are currently seeking a Research Fellow with experience in AI and machine learning research and development, with a focus on any or all of following application areas: Computer vision Generative AI
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the guidance of artificial intelligence techniques. The project will develop novel design processes that embed material behaviour within agent-based and machine learning computational design systems
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. Your expertise includes machine learning techniques such as Bayesian optimisation, and you’re comfortable working with experimental data, high-performance computing environments, and (ideally) thin film
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the Addiction & Impulsivity Research Lab and the Computational & Systems Neuroscience Lab . You will be part of a collaborative environment that integrates expertise in psychology, neuroscience and computational
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and beyond. About You We're seeking a passionate individual who thrives both independently in a research environment and as a collaborative member of the History program. As the successful candidate you
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to work independently and collaboratively. Advanced planning, time management, and written communication skills are essential, along with proven computer literacy and proficiency in relevant software and
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for drug discovery. Publishing peer-reviewed research and contributing to industrial software tools. About You To be successful in this role, you will have: A PhD in machine learning, computer
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Group’s research programme for the development of therapeutic biomolecules. You will work as part of a team using cutting edge synthetic techniques to develop safer drug targeting systems based