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revolutionising the field of temporal analytics. We have refocused the field on methods that are both effective and feasible for non-trivial problems. We received a prestigious best paper award at the SDM data
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written statement with your application outlining the necessity of conducting research in Japan, a coherent research plan approved by your supervisor and a detailed program for your research trip. How
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I am interested in the most catastrophic and explosive collisions in the Universe, such as the mergers of neutron stars and black holes. I study these using both gravitational waves and electromagnetic signatures, primarily focussed on linking the data from these exciting experiments with our...
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in organic and inorganic semiconductors ” (OPTEXC). As part of this program there is the opportunity for students to undertake fully funded joint degrees with the University of Bayreuth in Germany in
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Senior Engineer – Data Warehouse Development Job No.: 684248 Location: Clayton campus Employment Type: Full-time Duration: 2 year fixed-term appointment Remuneration: $120,138 - $132,610 pa HEW Level 08 (plus 17% employer superannuation) Amplify your impact at a world top 50 University Join our...
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program assisted greatly in framing my perspectives of Singapore and region, identifying problems faced but also developing the leadership skills to craft solutions to them. There is also significant heft
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relevant fields of specialisation for this appointment are operations research, operations management, or a closely related discipline with strong computational and/or mathematical skills with expertise in
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, Melbourne. We are seeking PhD candidates interested in developing methods to assist the formative assessment and improvement of collocated teamwork, by making multimodal activity traces visible and available
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researchers and postgraduate students. The role involves expanding the Faculty’s Higher Degree by Research (HDR) program by attracting top-tier candidates and building robust internal and external partnerships
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This Ph.D. project aims to combine causal analysis with deep learning for mental health support. As deep learning is vulnerable to spurious correlations, novel causal discovery and inference methods