1,748 data-"https:"-"https:"-"https:"-"https:"-"University-of-Rijeka" Fellowship positions
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institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences, and
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: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation
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scale. The successful candidate will be responsible for: safely shredding cells using a bespoke instrumented, stabilised shredder; recording data for LCA including mass and energy balances, energy and
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phases are as follows: Phase 1 – Literature reviews and research writing. Phase 2 – Survey and experiment design, and IRB applications. Phase 3 – Data collection and pre-processing. Phase 4 – Data analysis
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agrifood systems and experience in research, data analysis and stakeholder engagement. You will demonstrate initiative and the ability to work both independently and as part of multidisciplinary and
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in aeroacoustics, with a strong emphasis on data analysis and a deep understanding of aeroacoustics fundamentals. Demonstrate excellent communication skills, both written and verbal, as evidenced by
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. Cross-Disciplinary Fellowships (CDF) are for applicants with a Ph.D. from outside the life sciences (e.g. in physics, chemistry, mathematics, engineering or computer sciences), who have not worked in
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, you should address the "advantages" mentioned above, as these will be taken into account when ranking the candidates. the names and contact information for two referees. One of these should be the main
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. the names and contact information for two referees. One of these should be the main advisor for the master's thesis or equivalent thesis CV transcripts and diplomas showing completion of the bachelor's and
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industry, government, and professional bodies. This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic Performance . About the Food and Beverage