Research Fellow in Machine Learning for Cyber Security - JOBS.ac.kr(잡스) - 대한민국 최대 석박사 채용정보, 잡스!

{"job":{"jobId":1332419,"fk_accountId":null,"fk_organizationId":491,"fk_adminAccountId":null,"title":"Research Fellow in Machine Learning for Cyber Security","description":"\n\nWork type: Fixed Term\nLocation: Parkville\nDivision/Faculty: Melbourne School of Engineering\nDepartment/School: School of Computing and Information Systems\nSalary: $73,669 - $99,964 (Level A)\nRole &amp; Superannuation rate: Academic - Full time - 9.5% super\n\n\n<ul>\n<li>Bring your expertise in Machine Learning and Cyber Security to an exciting, collaborative research project</li>\n<li>Join Australia’s top-ranked Computer Science School and grow your research career</li>\n<li>2.5 year fixed-term contract, located in our world-leading innovation precinct</li>\n</ul>\n\n\nThe University of Melbourne is consistently ranked among the leading universities in the world, we are globally engaged; comprehensive; research-intensive; and committed to responding to the major challenges of our time.\n\n\nThe Melbourne School of Engineering (MSE) is strongly committed to supporting diversity and flexibility in the workplace. Improving the representation of women is necessary in our goal to innovate and to strengthen MSE’s reputation as a best-in-class centre of research.\n\n\nAbout the School of Computing and Information Systems (CIS) We are international research leaders with a focus on delivering impact and making a real difference in three key areas: data and knowledge, platforms and systems, and people and organisations.\n\n\nAt the School of Computing and Information Systems, you'll find curious people, big problems, and plenty of chances to create a real difference in the world.\n\n\nThe Opportunity\n\n\nMelbourne School of Engineering is seeking an emerging academic with a strong record of research in Deep Learning to contribute to an exciting ARC project focussed on cyber security. Applicants with a demonstrated research track record in deep learning will be highly-regarded. The role joins a collaborative team including investigators from RMIT and Deakin University and will conduct independent and co-operative research. There may also be opportunities to undertake teaching and contribute to other departmental activities.\n\n\nThe project is titled Learning the Focus of Attention to Detect Distributed Coordinated Attacks, the focus of this project is to devise a suite of novel attention mechanisms that can focus the search of machine learning techniques for cyber security. There are 3 key aims to the project:\n\n\n<ul>\n<li>Develop methods that incorporate threat intelligence to provide a temporal focus of attention in the search for emerging network-based attacks;</li>\n<li>Devise algorithms for dynamically sharing evidence between different networks to provide a spatial focus of attention in the collaborative detection of large-scale distributed attacks;</li>\n<li>Develop a theory for embedding a focus of attention explicitly in deep representation learning for event clustering and correlation in security analytics.</li>\n</ul>\n\n\nThe role will be located in our world-leading digital and data science innovation precinct, <a data-mz=\"\" href=\"https://www.youtube.com/watch?v=g6EJRbhl0U4\" rel=\"no-follow\">Melbourne Connect</a> - working from home in the first instance.\n\n\nAbout You\n\n\nYou will be passionate about your research area and motivated to produce high-quality outcomes for the project. You will bring an outstanding background in Machine Learning, especially in deep learning for graphs, and exposure to cyber-security. Your excellent interpersonal skills will enable to you to develop relationships with both internal and external partners.\n\n\nYou Will Have\n\n\n<ul>\n<li>A PhD in computer science or a relevant discipline; either completed or submitted;</li>\n<li>Demonstrated ability to perform independent research in machine learning and security analytics;</li>\n<li>Demonstrated expertise in the following areas will be highly regarded - deep representation learning and other deep learning methods, graph neural networks, anomaly detection and clustering (especially for graphs), attention-based neural networks;</li>\n</ul>\n\n\nWhat we offer you\n\n\nWe offer flexibility, whatever that may mean for you. Many of our benefit programs and onsite amenities are aimed at supporting you - including generous leave, child care subsidies, discounted parking, medical and health care. We offer extensive opportunities for personal and professional development, and we’ll support you in doing what you love.\n\n\nWe seek to increase the diversity of our workforce and the representation of all members of our community that have been traditionally under-represented.\n\n\nIf you’re curious, motivated and ready to undertake a meaningful and rewarding role we’re ready to meet you.\n\n\nHow to Apply\n\n\nApply online, upload your CV and complete the application form.\n\n\nPlease note that we are only able to accept applications from those with current working rights in Australia and who are not affected by travel restrictions.\n\n\nWhile we review your application, get to know us by visiting <a data-mz=\"\" href=\"http://www.eng.unimelb.edu.au/about/join-mse/why-join-mse\" rel=\"no-follow\">http://www.eng.unimelb.edu.au/about/join-mse/why-join-mse</a>\n\n\nThis is a re-advertised position. Previous applicants need not re-apply.\n\n\n<a data-mz=\"\" href=\"https://secure.dc2.pageuppeople.com/apply/422/gateway/default.aspx?sData=E7tTKDEyyWPyLsAhbioSIHJ8bh4aJXoOmX6sJF-U78evDr2ML6ioP7zjenzSU9xb0pCSD6r32kSBpcs0R8_cgzeeXqOJCTiTufTYNmmuGSXxnKcJsXZXptyd14E3LS_-xhUIaVW89YOswnDDtdK7NbnWMtSF_yU6JM8V2CmJdD8~\" rel=\"no-follow\">Position Description</a>\n\n\nApplications close: 25 Oct 2020 11:55 PM AUS Eastern Daylight Time\n\n\n","pdfUrl1":null,"location":"Melbourne, Australia","location1":"오세아니아","location2":null,"location3":null,"type":"2","applyUrl":"http://jobs.unimelb.edu.au/caw/en/job/903004/research-fellow-in-deep-learning-for-cyber-security","fileUrl1":null,"fileUrl2":null,"fileUrl3":null,"fileUrl4":null,"fileUrl5":null,"fileUrl6":null,"fileUrl7":null,"workingHour":"Full Time","contractType":"Fixed Term","salary":null,"original_id":"UNI|228769","original_domain":"https://www.timeshighereducation.com/unijobs","original_url":"https://www.timeshighereducation.com/unijobs/listing/228769/research-fellow-in-machine-learning-for-cyber-security/","original_isPremium":"false","closeType":2,"closedAt":null,"requireEducation":0,"managerTel":"","managerFax":null,"managerEmail":null,"managerName":"UNIVERSITY OF MELBOURNE","managerPhone":null,"managerAddress":null,"log_hit":8,"log_like":0,"publishState":1,"organizationName":null,"organizationName_en":null,"organizationName_alt":null,"createdAt":"2020-10-07T00:00:00.000Z","updatedAt":"2020-10-09T10:15:07.000Z"},"organization":{"organizationId":491,"lv1Id":null,"lv2Id":null,"name":"University of Melbourne","name_en":"The University of Melbourne","name_alt":",","introduction":"The University of Melbourne is the leading centre of higher education and research in Australia. Founded in 1853, it’s situated in the heart of the <a href=\"https://www.onlymelbourne.com.au/melbourne-worlds-most-liveable-city#.W3JmipMzZBw\">world’s most liveable cities.</a>&nbsp;With a strong research performance, excellence in learning and teaching, and intellectual and social capital, the University is consistently positioned with the world’s leading universities and currently ranked <a href=\"https://www.timeshighereducation.com/world-university-rankings/2018/world-ranking#!/page/1/length/25/sort_by/rank/sort_order/asc/cols/stats\">number one in Australia and number 32 in the world</a>.&nbsp;&nbsp;","logoImg":"","logoImgSquare":"https://s3.ap-northeast-2.amazonaws.com/jobs.ac.kr/dev/images/sakjdlsada_1210463820856.png","homepageUrl":"https://www.unimelb.edu.au/","infoUrl":"https://www.timeshighereducation.com/world-university-rankings/university-melbourne","country":"AU","state":"Victoria","location":"오세아니아","address":"Grattan Street, Parkville, Victoria, VIC 3010, Australia","phoneNumber":"+ (61 3) 9035 5511","faxNumber":"","type":1,"univType1":"대학","univType2":"대학교","univType3":"","univType4":"본교","establishedAt":"1853-01-05T00:00:00.000Z","count_majors":null,"count_students":null,"meta_competitiveness":"","publishState":1,"updatedAt":"2020-04-16T16:43:19.000Z","createdAt":"2020-03-04T20:13:07.000Z","default_1_bannerImage":null,"default_1_bannerImageMobile":null,"default_2_bannerImage":null,"default_2_bannerImageMobile":null,"default_3_bannerImage":null,"default_3_bannerImageMobile":null}}