66 coding-"https:"-"FEMTO-ST"-"CSIC"-"U" "https:" "https:" "https:" "https:" "P" positions at Monash University
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sensing equipment and theoretical work around play. For more information see http://exertiongameslab.org
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information see http://exertiongameslab.org
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We have a range of potential research projects on offer in partnership with VIFM - https://www.vifm.org/ - looking at ML techniques in predicting forensic diagnoses / image analysis, across
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qualitative and quantitative methods. Work on WP-2 will suit someone with an interest and aptitude for coding administrative data using large language models. It will require use of advanced quantitative
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provide multiple competitive scholarships funded by a national elite HDR training program: Data61 Next Generation Graduate (https://www.csiro.au/en/work-with-us/funding-programs/programs/next-generation
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information on our practice-based PhD program, please see: https://sensilab.monash.edu/work-with-us/practice-based-phd/
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., Gorthi A., Wang L., et.al. Predicting drug response of tumors from integrated genomic profiles by deep neural networks. 2019. BMC Medical Genomics volume 12, Article number: 18 Luo P., Ding Y., Lei X., Wu
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contrastive self-supervised learning task to learn from massive amounts of EEG data. Frontiers in human neuroscience. [2] https://www.emotiv.com
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: 04EX783), pp439-444 Frey and Osborne (2013) Frey and Osborne (2017) P. J. Tan and D. L. Dowe (2003). MML Inference of Decision Graphs with Multi-Way Joins and Dynamic Attributes, Proc. 16th Australian Joint
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the endless possibilities of digital sound, allowing the plucking of sounds out of thin air. URLs and Further Reading https://airsticks.xyz/ Ilsar, A.A., 2018. The AirSticks: a new instrument for live