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Vacancies within Nuffield Department of Obstetrics and Gynaecology

There are currently 2 vacancies within Nuffield Department of Obstetrics and Gynaecology:

Title Closes Salary
Senior Fellow in Women’s Health July 5, 2017, noon Grade E82: £76,761 - £103,490 p.a.
Machine Learning Scientist (two posts) July 10, 2017, noon Grade 8: £39,324 - £46,924 p.a.

Senior Fellow in Women’s Health

Closes: July 5, 2017, noon; salary: Grade E82: £76,761 - £103,490 p.a.

<div> <p></p><p>The Nuffield Department of Obstetrics and Gynaecology (NDOG) invites applications for a full-time, fixed-term appointment as a Senior Fellow in Women's Health.</p><br> <p>Your duties will be divided so that approximately 50% of the 10 PA job-plan will be spent on academic pursuits and the other 50% on clinical duties. You will be expected to make a significant contribution to research in the field of the molecular basis and clinical management of cervical dysplasia in addition to contributing to undergraduate and graduate teaching, examining and research supervision.</p><br> <p>Your principal weekly clinical duties at the John Radcliffe Hospital, as an honorary consultant, will include two colposcopy sessions as Clinical Lead for Colposcopy services, a day-case operating session, administration plus other duties in gynaecology to be mutually agreed with the Clinical Director.</p><br> <p>You will need full GMC registration, CCT or equivalent qualification and BSCCP accreditation in addition to a doctorate, a publication record in peer-reviewed journals and relevant postdoctoral research.</p><br> <p>This is a fixed-term role for 5 years.</p><br> <p>You will be required to upload a supporting statement and CV as part of your online application.</p><br> <p>Only applications received before 12.00 midday on Wednesday 5 July 2017 can be considered. Interviews are expected to be held on Friday 28 July 2017.</p> </div>

Machine Learning Scientist (two posts)

Closes: July 10, 2017, noon; salary: Grade 8: £39,324 - £46,924 p.a.

<div> <p></p><p>Do you have expertise in Machine Learning? Could you use this experience to help us create game-changing solutions for healthcare problems?</p><br> <p>The George Institute for Global Health, part of the Nuffield Department of Obstetrics and Gynaecology, is looking for two Machine Learning Scientists to join the team and contribute to the development and implementation of the algorithmic core of a series of exciting new projects in Oxford Martin School&#8217;s prestigious program on Deep Medicine. The program is focused on solving high-impact healthcare problems, with the application of modern machine learning algorithms to large multi-modal (e.g. genetics, imaging, medical records) biomedical datasets.</p><br> <p>Your responsibilities will include employing the existing (and developing new) Machine Learning algorithms that can find patterns in large multi-modal data, innovating and providing solutions for the delivery of care (e.g., by designing and undertaking research projects that translate complex healthcare problems into Machine Learning problems) and participating in, leading, and creating cross-functional research projects (and training).</p><br> <p>You will hold a PhD/DPhil (or close to completion) in computer science engineering or in a related field. You will have scientific expertise and applied experience in machine learning, in depth understanding of common machine learning algorithms and track record in advanced topics of machine learning. You will also have advanced programming skills in Python and/or R, practical experience in preparing data for machine learning and you will have completed at least one significant project in applied machine learning. Real-world experience in deep learning, integration of machine learning algorithms with big-data platforms (e.g. Spark) and high-performance computing ecosystems (e.g., CUDA) as well as Programming in C++ and Java would also be an advantage.</p><br> <p>These positions are full-time and fixed-term for 2 years, with the possibility of further extension. These posts are available immediately; ideally we would like somebody in post by September 2017 or as soon as possible thereafter.</p><br> <p>You will be required to upload a CV and supporting statement as part of your online application.</p><br> <p>The closing date for applications is 12.00 noon on Monday 10 July 2017. Interviews are expected to take place on Wednesday 12 July 2017.</p> </div>