268 parallel-processing-bioinformatics-"Multiple" Fellowship research jobs in Australia
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 days ago
opportunities to people of all backgrounds and identities. For more information about staff equity at ANU, click here . For enquiries about the application process, or if you require reasonable adjustment
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via the academic promotions process. Questions? For more information about this opportunity, please contact Professor Paul Dux at p.dux@psy.uq.edu.au . For application inquiries, please reach out
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in sequential decision-making approaches such as Markov Decision Processes, reinforcement learning, deep learning, or adaptive management. You have a strong track record of research publications and
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the academic promotions process. Questions? For more information about this opportunity, please contact Dr. David Kainer, d.kainer@uq.edu.au. For application inquiries, please reach out to the Talent Acquisition
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applying, please reach out to the contact person in the Position Description. Setting you up for success We are committed to providing a recruitment process that is fair, equitable and accessible to everyone
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linguistically diverse people, people with disabilities, neurodivergent people, and people of all genders, sexualities, and age groups. We are committed to fostering an inclusive and accessible recruitment process
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including hybrid on site/WFH options and flexible start/finish times, and genuine career progression opportunities via the academic promotions process. About You Completion or near completion of a PhD in
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in advanced signal processing techniques and good understanding of emerging machine learning methodologies used in NDE. You will work in close collaboration with project partners at the University
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. We are committed to fostering an inclusive and accessible recruitment process at Monash. If you need any reasonable adjustments, please contact us at hr-recruitment@monash.edu in an email titled
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-quality research publications in econometrics or related fields. You will possess the ability to solve complex statistical problems, show advanced computer literacy with proficiency in relevant software