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Research Assistant - Biomedical Imaging and Artificial Intelligence
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Nuffield Department of Population Health
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The Nuffield Department of Population Health (NDPH) contains world renowned population health research groups and provides an excellent environment for multi-disciplinary research and teaching. We are seeking a Research Assistant to be part of a team working on biomedical imaging, multiple aspects of machine learning and analysis methods. The primary focus of this role is to develop novel biomedical image analysis and machine learning methods to analyse computed tomography (CT) and positron emission tomography (PET)/CT scans to identify therapy-resistant disease of lung cancer. You will be responsible for managing your own research and administrative activities, contribute to wide project planning and gather/analyse data. To be considered, you will hold an Master’s degree in life sciences, engineering, mathematics or computational, have experience in the use of biomedical/clinical imaging data, have proven experience in programming (Python preferably) for medical imaging processing and machine learning and excellent organisational skills, as well as a good team player. This is a full time, fixed term post (part time considered) for 18 months. The closing date for applications is noon on 17th January 2024. You will be required to upload a CV and a cover letter as part of your online application. The cover letter should clearly describe how you meet each of the selection criteria listed in the job description.
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Standard Grade 6: £32,332 - £38,205 per annum
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Oxford Population Health (Nuffield Department of Population Health, University of Oxford), Old Road Campus, Headington, Oxford, OX3 7LF
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Research Assistant - Biomedical Imaging and Artificial Intelligence JD
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Job description Job title Research Assistant - Biomedical Imaging and Artificial Intelligence Division Medical Sciences Division Department Oxford Population Health (Nuffield Department of Population Health, University of Oxford) Location Old Road Campus, Headington, Oxford, OX3 7LF Grade and salary Grade 6: £32,332 - £38,205 per annum Hours Full time (Part time considered) Contract type Fixed-term – 18 months Vacancy reference 169875 Research Assistant in Biomedical Imaging & Artificial Intelligence JD - December 2023 1 About Oxford Population Health Oxford Population Health (the Nuffield Department of Population Health) provides an excellent environment for multi-disciplinary research and teaching and for professional and support staff. We work together to answer some of the most important questions about the causes, prevention and treatment of disease. The Department has around 900 staff, students and academic visitors working in a number of world-renowned population health research groups, including the Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), the Cancer Epidemiology Unit (CEU), the National Perinatal Epidemiology Unit (NPEU) and other groups working on public health, health economics, ethics and health record linkage. It is also a key partner in the Oxford University’s Big Data Institute. In the 2021 Research Excellence Framework (REF), 96% of the research submitted to Unit of Assessment 2: Public Health, Health Services and Primary Care, was ranked either 4* (world-leading in terms of originality, significance and rigour) or 3* (internationally excellent in terms of originality, significance and rigour). This comprised research from Oxford Population Health and research from the Nuffield Department of Primary Care Health Sciences. We scored particularly well for having an environment that is conducive to producing research of world-leading quality and enabling outstanding impact, in terms of its vitality and sustainability. In addition to its research activities, the Department is home to the MSc in Global Health Science and Epidemiology, the MSc in Clinical Trials, and a variety of short courses. Students also come to undertake research for DPhil degrees. Teaching is provided for undergraduates reading for Medicine and for public health doctors in specialist training. For more information please visit the Oxford Population Health website. About the Medical Sciences Division The Medical Sciences Division is an internationally recognised centre of excellence for biomedical and clinical research and teaching, and the largest academic division in the University of Oxford. World-leading programmes, housed in state-of-the-art facilities, cover the full range of scientific endeavour from the molecule to the population. With our NHS partners we also foster the highest possible standards in patient care. For more information please visit the Medical Sciences Division website. About the University of Oxford Welcome to the University of Oxford. We aim to lead the world in research and education for the benefit of society both in the UK and globally. Oxford’s researchers engage with academic, commercial and cultural partners across the world to stimulate high-quality research and enable innovation through a broad range of social, policy and economic impacts. We believe our strengths lie both in empowering individuals and teams to address fundamental questions of global significance, while providing all our staff with a Research Assistant in Biomedical Imaging & Artificial Intelligence JD - December 2023 2 welcoming and inclusive workplace that enables everyone to develop and do their best work. Recognising that diversity is our strength, vital for innovation and creativity, we aspire to build a truly diverse community which values and respects every individual’s unique contribution. While we have long traditions of scholarship, we are also forward-looking, creative and cutting-edge. Oxford is one of Europe's most entrepreneurial universities and we rank first in the UK for university spin-outs, and in recent years we have spun out 15-20 new companies every year. We are also recognised as leaders in support for social enterprise. Join us and you will find a unique, democratic and international community, a great range of staff benefits and access to a vibrant array of cultural activities in the beautiful city of Oxford. For more information please visit the Oxford University website. The Big Data Institute The Oxford University Big Data Institute (BDI) is an interdisciplinary research centre aiming to develop, evaluate and deploy efficient methods for acquiring and analysing biomedical data at scale and for exploiting the opportunities arising from such studies. For more information please visit: http://www.bdi.ox.ac.uk/ The role The postholder will be part of a team working on biomedical imaging, multiple aspects of machine learning and analysis methods. The primary focus of this role is to develop novel biomedical image analysis and machine learning methods to analyse computed tomography (CT) and positron emission tomography (PET)/CT scans to identify therapy-resistant disease of lung cancer. Current clinical imaging methods that measure changes in tumour size (e.g. CT scan), or alterations in tumour glycolytic metabolism (e.g. [18F]FDG PET/CT), require multiple treatment cycles to confidently detect therapy resistance. Here, in collaboration with King’s College London, University of Newcastle, and University of Cambridge, we will be developing a combination of innovative whole-body imaging techniques and advanced artificial intelligence (AI) methods to automate quantification of the tumour volume readouts and predict therapy resistance of individual lesions. AI/ML–aided methods in medical imaging can improve the accuracy and efficiency of cancer diagnosis and treatment. Traditionally, obtaining reliable and consistent readouts from multimodal imaging (e.g. PET/CT) is time-consuming and dependent on intra- and inter-reader observer biases. Moreover, preclinical imaging of the lung additionally suffers from inherent motion and breathing artefacts which may confound results. Automated, accurate, and unbiased quantification of tumours is therefore essential for the translation of [18F]FSPG PET into existing clinical pathways and for the identification of therapy-resistance disease. This post provides an exciting opportunity to work with unique imaging data to address one of the biggest challenges facing cancer patient management, and join a multi-disciplinary team employing quantitative approaches to novel biomedical problems. The is an excellent opportunity for someone with a quantitative background, who would like to gain experience working with a research team on challenging data science projects. The candidate will report directly to the Oxford study PI, Associate Professor Bartek Papiez. Research Assistant in Biomedical Imaging & Artificial Intelligence JD - December 2023 3 Responsibilities  Manage own research and administrative activities, within guidelines provided by senior colleagues.  Contribute to wider project planning, including ideas for new research projects.  Gather, validate and analyse quantitative data from a variety of sources, and identify suitable alternatives where research material is restricted.  Contribute to the design of research methods, analytical tools and resources appropriate to the work in collaboration with members of the research team.  Contribute to systematic literature reviews, writing up results for research publications and reviews, conferences or meetings.  Responsible for the day-to-day administration of research projects.  Build and maintain effective communications and relationships and represent the research group at internal/external meetings and seminars.  Contribute to discussions and share research findings with colleagues in partner institutions, and research groups.  Act as the primary interface between the different data analytical and data provisioning teams, being a key source of information and providing advice to other members of the group on methodologies or procedures. The above list is not exhaustive and the role-holder is required to undertake such duties as may reasonably be requested within the scope of the post. All staff are required to act in a professional, cooperative and flexible manner, in line with the requirements of the post. Selection criteria Essential        An Masters degree in life sciences, engineering, mathematics or computational. Proven experience in programming (Python preferably) for medical imaging processing and machine learning. Demonstrated experience in the use of biomedical/clinical imaging data (in particular PET/CT) Excellent organisational and prioritisation skills. Excellent written and oral communication skills including ability to present complex information in a concise and clear manner to people from different backgrounds. Flexible, pro-active and adaptable team worker. Experience of source control, particularly Git/GitLab Desirable   Experience of contributing to research publications Experience of contributing ideas for new research projects Research Assistant in Biomedical Imaging & Artificial Intelligence JD - December 2023 4  Experience of working in a multidisciplinary team (e.g. a team involving clinicians, scientists, etc.) and/or in wider collaborative groups Pre-employment screening Standard checks If you are offered the post, the offer will be subject to standard pre-employment checks. You will be asked to provide: proof of your right-to-work in the UK; proof of your identity; and (if we haven’t done so already) we will contact the referees you have nominated. You will also be asked to complete a health declaration so that you can tell us about any health conditions or disabilities for which you may need us to make appropriate adjustments. Please read the candidate notes on the University’s pre-employment screening procedures. How to apply Applications are made through our e-recruitment system and you will find all the information you need about how to apply on our Jobs website. Your application will be judged solely on the basis of how you demonstrate that you meet the selection criteria stated in the job description. As part of your application you will be asked to provide details of two referees and indicate whether we can contact them now. You will be asked to upload a CV and a supporting statement. The supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. This may include experience gained in employment, education, or during career breaks (such as time out to care for dependants). Please upload your CV and supporting statement as PDF files with your name and the document type in the filename. All applications must be received by midday UK time on the closing date stated in the online advertisement. Information for priority candidates A priority candidate is a University employee who is seeking redeployment because they have been advised that they are at risk of redundancy, or on grounds of illhealth/disability. Priority candidates are issued with a redeployment letter by their employing departments. Research Assistant in Biomedical Imaging & Artificial Intelligence JD - December 2023 5 If you are a priority candidate, please ensure that you attach your redeployment letter to your application (or email it to the contact address on the advert if the application form used for the vacancy does not allow attachments). If you need help Help and support is available from the HR Systems Recruitment support webpage. If you require any further assistance please email the Recruitment Support team. To return to the online application at any stage, please go to the University’s recruitment website. Please note that you will receive an automated email from our e-recruitment system to confirm receipt of your application. Please check your spam/junk mail if you do not receive this email. Important information for candidates Data privacy Please note that any personal data submitted to the University as part of the job application process will be processed in accordance with the GDPR and related UK data protection legislation. For further information, please see the University’s Privacy Notice for Job Applicants. The University’s Policy on Data Protection is available on the University’s Compliance webpages. The University’s policy on retirement The University operates an Employer Justified Retirement Age (EJRA) for very senior research posts at grade RSIV/D35 and clinical equivalents E62 and E82, which with effect from 1 October 2023 will be 30 September before the 70th birthday. The justification for this is explained at: https://hr.admin.ox.ac.uk/the-ejra. For existing employees on these grades, any employment beyond the retirement age is subject to approval through the procedures: https://hr.admin.ox.ac.uk/the-ejra. There is no normal or fixed age at which staff in posts at other grades have to retire. Staff at these grades may elect to retire in accordance with the rules of the applicable pension scheme, as may be amended from time to time. Equality of opportunity Entry into employment with the University and progression within employment will be determined only by personal merit and the application of criteria which are related to the duties of each particular post and the relevant salary structure. In all cases, ability to perform the job will be the primary consideration. No applicant or member of staff shall be discriminated against because of age, disability, gender reassignment, marriage or civil partnership, pregnancy or maternity, race, religion or belief, sex, or sexual orientation. Research Assistant in Biomedical Imaging & Artificial Intelligence JD - December 2023 6 Research Assistant in Biomedical Imaging & Artificial Intelligence JD - December 2023 7 Benefits of working at the University Employee benefits University employees enjoy 38 days’ paid holiday, generous pension schemes, travel discounts, and a variety of professional development opportunities. Our range of other employee benefits and discounts also includes free entry to the Botanic Gardens and University colleges, and discounts at University museums. University Club and sports facilities Membership of the University Club is free for all University staff. The University Club offers social, sporting, and hospitality facilities. Staff can also use the University Sports Centre on Iffley Road at discounted rates, including a fitness centre, powerlifting room, and swimming pool. Information for staff new to Oxford If you are relocating to Oxfordshire from overseas or elsewhere in the UK, the University's Welcome Service website includes practical information about settling in the area, including advice on relocation, accommodation, and local schools. There is also a visa loan scheme to cover the costs of UK visa applications for staff and their dependents. Family-friendly benefits With one of the most generous family leave schemes in the Higher Education sector, and a range of flexible working options, Oxford aims to be a family-friendly employer. We also subscribe to the Work+Family Space, a service that provides practical advice and support for employees who have caring responsibilities. The service offers a free telephone advice line, and the ability to book emergency back-up care for children, adult dependents and elderly relatives. Childcare The University has excellent childcare services, including five University nurseries as well as University-supported places at many other private nurseries. For full details, including how to apply and the costs, see the Childcare Services webpages. Disabled staff We are committed to supporting members of staff with disabilities or long-term health conditions. For further details, including information about how to make contact, in confidence, with the University’s Staff Disability Advisor, see the Disability Support webpages. Staff networks The University has a number of staff networks including the Oxford Research Staff Society, BME staff network, LGBT+ staff network and a disabled staff network. You can find more information on the Equality and Diversity at Oxford webpages. The University of Oxford Newcomers' Club The University of Oxford Newcomers' Club is an organisation run by volunteers that aims to assist the partners of new staff settle into Oxford, and provides them with an opportunity to meet people and make connections in the local area. 8
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