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Field
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unresolved challenges in sampling design, DNA recovery, and signal variability. Towards this end, CSIRO has recently formed a multidisciplinary team, in collaboration with the Minderoo Foundation, dedicated
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Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience working with clinical data
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for your first independent position and grant or identify connections into the healthcare or private sector to kickstart your next career move. You will be mentored by Dr. Philipp Lange, PhD (Canada Research
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with the potential to collaborate in developing competitive research grant applications. Applicants must indicate the Research Cluster(s) concerned in their research proposal. Job Description Researchers
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digital signal processing, control systems, and embedded AI for biological applications. Experience with AI/ML development frameworks, model deployment pipelines, and simulation environments for behavior
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will develop a novel modelling framework that translates climate signals to support cost-optimal long-term investment decisions, while also considering operational feasibility. The successful candidate
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Signal Processing and Wireless Communications (PSC) - Good knowledge - 20 points. - Little knowledge - 10 points. - No mention of specific knowledge in the area - 0 points d) Experience and general
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Experience To be considered for this position, you will have: Completion of a PhD in a relevant discipline e.g psychology, ergonomics and human factors, public health. Evidence of experience in research and
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), or for application process queries Ruikang Xue (ruikang.xue@ucl.ac.uk). About you The successful candidate will have a PhD qualification, extensive knowledge and expertise in additive manufacturing, surface and bulk
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is based on a previous qualifying position PhD Fellow, research assistant, or the like in such a way that the total time used for research training amounts to three years. We process personal data