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聯(lián)邦科學(xué)與工業(yè)研究組織圖像分析方向方向博士后職位招聘

時間:2020-03-13來源:中國博士人才網(wǎng) 作者:佚名

  聯(lián)邦科學(xué)與工業(yè)研究組織圖像分析方向方向博士后職位招聘

  Develop innovative machine learning methods (deep learning) for the analysis of images.

  • Represent CSIRO at leading national and international conferences and forums.

  • Join CSIRO’s Data61, the largest data innovation group in Australia

  Join the Imaging and Computer vision Group at the CSIRO’s Data61, joining 600 other data science scientists building innovative solutions for Australia. In this role, you will develop innovative machine learning methods (deep learning) for the analysis of images. Several projects are available including medical image analysis, 3D object detections, and human pose estimation. Aspects involving spatio-temporal modelling and tracking are of high importance for our research. Be supported by a large team comprising many post-graduate students and be involved in their supervisions.

  More specifically you will:

  • Develop innovative concepts, theories, tools and techniques related to the analysis of video and still images.

  • Harness the growing volume of publicly available data sources, as well as work on establishing proprietary datasets in collaboration with our partners.

  • Produce high quality scientific and technical outputs including journal articles, conference papers and presentations, patents and technical reports.

  • Represent CSIRO at leading national and international conferences and forums.

  Location: Canberra, ACT or Sydney, NSW

  Tenure: Specified term of 3 years

  Salary: AU$83K – AU$94K + up to 15.4% superannuation

  Reference: 65851

  To be successful you will need:

  Under CSIRO policy only those who meet all essential selection criteria can be appointed.

  • A doctorate (or will shortly satisfy the requirements of a PhD) in a relevant discipline area, such as computer vision or medical image analysis.

  o Please note: To be eligible for this role you must have no more than 3 years (or part time equivalent) of postdoctoral research experience.

  • Demonstrated experience in 3D computer vision such as

  o reconstruction, visual localisation and mapping,

  o human pose detection and analysis,

  o semantic vision with reasoning about the 3D world, and

  o understanding visual scenes over time, or advanced deep learning methodology applied to medical image analysis.

  • Strong experience with scientific computing platform and programming languages such as Python, Matlab, C++, PyTorch, Tensorflow.

  • High level written and oral communication skills with the ability to represent the research team effectively internally and externally, including the presentation of research outcomes at national and international conferences.

  • A sound history of publication in peer reviewed journals and/or authorship of scientific papers, reports, grant applications or patents.

  • A record of science innovation and creativity, including the ability & willingness to incorporate novel ideas and approaches into scientific investigations.

  The successful applicant may be required to obtain and provide a National Police Check or equivalent.

  For more information please view the Position Description.

  We’re working hard to recruit diverse people and ensure all our people feel supported to do their best work and empowered to let their ideas flourish.

  Flexible Working Arrangements

  We work flexibly at CSIRO, offering a range of options for how, when and where you work. Talk to us about how this role could be flexible for you.

  About CSIRO

  At CSIRO you can be part of helping to solve big, complex problems that make a real difference to our future. We spark off each other, learn from each other, trust each other and collaborate to achieve more than we could individually in a supportive, rewarding, inclusive and truly flexible environment.

  Apply Online

  To apply online, please provide a CV and a response to criteria outlining your suitability and motivation for the role.

  Applications Close

  Wednesday, 8th April 2020 at 11:59PM AEST

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