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spatial transcriptomics to link molecular signatures with tissue architecture. Develop predictive models for disease diagnosis, prognosis, and therapeutic targeting. Experimental and Analytical Approaches
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
inference and/or machine-learning approaches. You will be able to articulate and prosecute an innovative interdisciplinary research vision, contribute new modelling or analytical methods, and integrate
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to complete the doctoral program within the employment period When assessing applications, particular importance will be attached to: Formal qualifications Analytical skills Language skills The personal
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an advantage if you have Interest in the mechanical behavior of materials. Experience with machine learning and/or programming/coding. Experience with finite element modeling from civil, mechanical, or marine
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machine learning and AI acceleration. Perform performance, power, and area (PPA) analysis of processor and accelerator designs. Publish research findings in top-tier conferences and journals and contribute
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superlattices (twistronics). The role will focus on developing and applying theoretical models and computational quantum chemistry and machine learning methods to uncover novel properties and phenomena in low
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efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all
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Geosciences division is hiring an Autonomous Material Processing Postdoctoral Fellow to help transform how critical materials are produced. In this role, you'll bring together machine learning, real-time
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as an integrated analytical framework, we apply comparative risk assessment, disease modeling, machine learning, and survival extrapolation methods to systematically quantify the long-term impacts