Vacancies within Nuffield Department of Women's and Reproductive Health
There are currently 3 vacancies within Nuffield Department of Women's and Reproductive Health:
| Title | Closes | Salary |
|---|---|---|
| Part-time Programme Manager - Women's Health UK | Aug. 22, 2018, noon | Grade 7: £31,076 - £38,183 with a discretionary range to £41,709 p.a. (pro rata) |
| Postdoctoral Fellow in the Statistical Aspects of Early Human Growth and Development | Sept. 10, 2018, noon | Grade 7: £31,604 - £38,833 with a discretionary range to £42,418 p.a. |
| Research Assistant in Machine Learning | Sept. 10, 2018, noon | Grade 6: £28,098 - £33,518 with a discretionary range to £36,613 p.a. (pro rata for part-time) |
Part-time Programme Manager - Women's Health UK
Closes: Aug. 22, 2018, noon; salary: Grade 7: £31,076 - £38,183 with a discretionary range to £41,709 p.a. (pro rata)
<div> <p></p><p>The George Institute for Global Health (UK), part of the Nuffield Department of Women’s & Reproductive Health, is looking for a Programme Manager who is passionately committed to improving the world for women, to coordinate our Women’s Health Programme (WHP) in the UK.</p><br> <p>In 2016, in association with the Oxford Martin School at the University of Oxford, The George Institute launched a policy paper in which we called for a new global agenda on women’s health. This paper extends the current focus on sexual and reproductive health to include the leading causes of death and disability for women and girls, namely non-communicable diseases (NCDs) and injuries. We also called for a greater focus on sex-disaggregated analyses of large health databases, informed by a gender lens. In support of the recommendations in that paper, our aim is to establish a cross-regional, cross-divisional women’s health programme (WHP) that will, in the longer term, be respected for its contributions to improving women’s health worldwide. The focus areas of the George Institute WHP global programme are: (i) conditions specific for women; and (ii) NCDs and injury in women. Currently, we have major programmes in gender- and sex-disaggregated research, and the link between pregnancy conditions and NCDs, with emerging programmes in several other areas related to the programme focus. It is hoped the WHP will incorporate discovery research, translational research, advocacy and thought leadership, and capacity building across the focus areas.</p><br> <p>Your responsibilities will include: identifying and creating a formal structure for students and academics interested in and/or currently working on projects that support the WHP at TGI (UK) and NDWRH to come together; developing, implementing and promoting regular meetings and communications within this group, aiming to raise the profile of the WHP in the University of Oxford and across the UK; identifying strategic partners working in global women’s health in the UK who could further the strategic objectives of the WHP.</p><br> <p>You will have a master’s degree in public health, epidemiology, international women’s health, gender studies, development or in a relevant health or social science discipline and experience working in multidisciplinary teams, managing relationships with external partners and engaging senior stakeholders. You will be available and willing to undertake national and international travel and will have strong written and verbal communications skills. You will have cultural competence and an ability to work in multicultural teams, passion in the field of women’s health and a commitment to gender equity and appreciation of diversity. IT skills, the ability to see the big picture, being flexible and adaptable in the face of changing organisational priorities and ambiguous environments and managing work independently without close supervision are also essential in this role.</p><br> <p>This position is part-time (18.75 hours/0.5 FTE) and fixed-term for 12 months in the first instance. This post is available as soon as possible. Applications for flexible working arrangements are welcomed and will be considered in line with business needs.</p><br> <p>You will be required to upload a CV and supporting statement.</p><br> <p>The closing date for applications is 12.00 noon on Wednesday 22 August 2018.</p> </div>Postdoctoral Fellow in the Statistical Aspects of Early Human Growth and Development
Closes: Sept. 10, 2018, noon; salary: Grade 7: £31,604 - £38,833 with a discretionary range to £42,418 p.a.
<div> <p></p><p>The Nuffield Department of Women’s & Reproductive Health is looking for a Postdoctoral Fellow in the Statistical Aspects of Early Human Growth and Development to join the INTERBIO-21st team. The INTERBIO-21st Study is an extension to the International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st) Project. The study aims to improve the phenotypic characterisation of the intrauterine growth restriction/small for gestational age (IUGR/SGA) and preterm birth syndromes at clinical, biochemical and omic levels so as to develop better strategies to correct the short and long-term effects of an adverse intrauterine environment (www.interbio21.org.uk and https://intergrowth21.tghn.org).</p><br> <p>You will be an integral part of the team with responsibility for the analysis primarily of the extensive clinical data from the INTERBIO-21st Study. You will be expected to carry out the final steps of data cleaning and file preparation as required by the analytical and publication strategy of the project. You will also be expected to provide methodological and analytical advice on INTERBIO-21st sub-studies and other projects in the field of women’s health.</p><br> <p>You will have a PhD (or near completion) in statistics, epidemiology, or a related field including an important quantitative component, and will have knowledge and/or experience of design and analysis, interpretation and reporting of clinical studies. You will be able to communicate (both verbally and in writing) statistical information in a non-technical way, to investigate complex problems and develop solutions and to read and assimilate medical and statistical research literature. A proficiency in using the main statistical packages (e.g. STATA or SAS) as well the ability to manage multiple simultaneous projects, prioritise short and long-term goals, and deliver within deadlines are essential for this role.</p><br> <p>This position is full-time and fixed-term for 2 years, with the possibility of extension. Applications for flexible working arrangements are welcomed and will be considered in line with business needs.</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 September 2018.</p> </div>Research Assistant in Machine Learning
Closes: Sept. 10, 2018, noon; salary: Grade 6: £28,098 - £33,518 with a discretionary range to £36,613 p.a. (pro rata for part-time)
<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 Women’s & Reproductive Health, is looking for a Research Assistant in Machine Learning 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’s prestigious programme on Deep Medicine. The programme is focused on tackling major healthcare problems, with the application of modern machine learning algorithms to large-scale multi-modal (e.g. genetics, medical imaging, medical records, remote sensing) datasets.</p><br> <p>You will hold an MSc/MEng (or near completion) in computer science engineering, statistics, or in a relevant area. You will also have some applied experience in machine learning, understanding of common machine earning algorithms (e.g. for classification, regression and clustering) and programming skills in Python and/or R (and their related data processing, machine learning, and visualisation libraries). Practical experience in preparing data for machine learning, completion of at least one significant project (e.g. a Master’s research project) and the ability to work independently and show initiative as part of the team are also essential for this role.</p><br> <p>This position can be offered full-time or part-time (at least 60% FTE, 22.5 hours) and fixed-term for 2 years, with the possibility of further extension. Applications for flexible working arrangements are welcomed and will be considered in line with business needs.</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 September 2018.</p> </div>