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We are seeking to recruit to the post of Training Director for the Africa-India-Oxford Schmidt AI in Science Faculty Fellowship Programme.

 

As Training Director, you will use your research expertise in AI/Machine Learning (ML) working closely with the Academic Director, the Africa Oxford Centre, and the Oxford India Centre for Sustainable Development, to develop and deliver the training programme for this exciting new programme which builds on Oxford’s existing Schmidt AI in Science Postdoctoral Fellowship Programme. The new programme spans the interdisciplinary research of the departments within the Mathematical, Physical and Life Sciences Division at Oxford.

 

The Programme will recruit outstanding scientists (Fellows) from under-resourced settings in Africa and India and will build an inclusive community of researchers with excellent understanding of AI/ML techniques and their application to scientific research. It will provide tailored training in AI/ML and professional skills to enable the Fellows to achieve their research goals.

 

With the support of the Programme Administrator, you will be responsible for the day to day running and monitoring of the training programme, ensuring that it is relevant, focused and fulfills the requirements of the Faculty Fellows.

 

You will help develop and support a comprehensive programme of career and professional development activities and will develop and deliver activities which foster the cohort ethos and which support the EEDI aims of the programme.

 

This part time role (50%) can be matched with existing funding to create a full-time post for an extended period of time and could therefore suit post-holders of postdoctoral fellowships, subject to approval by the funding body and if the candidate holds a fellowship at the University of Oxford, the department(s)/college where the fellowship is held.

 

Information on the Oxford Schmidt AI in Science Postdoctoral Fellowship Programme is available at: SAIIS

 

Information on the Africa-India-Oxford Schmidt AI in Science Faculty Fellowship Programme (AI2-Ox SFF) is available at: AI2-Ox SFF

 
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"NTriples description of Training Director, Schmidt AI in Science Africa-India-Oxford Faculty Fellowship Programme" . . _:N51832e2a0a4947e583933ddea4598986 . . . "sous-Organization de"@fr . . _:N2727cab08d2f4740a5b62d7f3d81f2c4 "United Kingdom" . . "false"^^ . . _:N2727cab08d2f4740a5b62d7f3d81f2c4 "Wellington Square" . . """We are seeking to recruit to the post of Training Director for the Africa- India-Oxford Schmidt AI in Science Faculty Fellowship Programme. As Training Director, you will use your research expertise in AI/Machine Learning (ML) working closely with the Academic Director, the Africa Oxford Centre, and the Oxford India Centre for Sustainable Development, to develop and deliver the training programme for this exciting new programme which builds on Oxford’s existing Schmidt AI in Science Postdoctoral Fellowship Programme. The new programme spans the interdisciplinary research of the departments within the Mathematical, Physical and Life Sciences Division at Oxford. The Programme will recruit outstanding scientists (Fellows) from under- resourced settings in Africa and India and will build an inclusive community of researchers with excellent understanding of AI/ML techniques and their application to scientific research. It will provide tailored training in AI/ML and professional skills to enable the Fellows to achieve their research goals. With the support of the Programme Administrator, you will be responsible for the day to day running and monitoring of the training programme, ensuring that it is relevant, focused and fulfills the requirements of the Faculty Fellows. You will help develop and support a comprehensive programme of career and professional development activities and will develop and deliver activities which foster the cohort ethos and which support the EEDI aims of the programme. This part time role (50%) can be matched with existing funding to create a full-time post for an extended period of time and could therefore suit post- holders of postdoctoral fellowships, subject to approval by the funding body and if the candidate holds a fellowship at the University of Oxford, the department(s)/college where the fellowship is held. Information on the Oxford Schmidt AI in Science Postdoctoral Fellowship Programme is available at: SAIIS Information on the Africa-India-Oxford Schmidt AI in Science Faculty Fellowship Programme (AI2-Ox SFF) is available at: AI2-Ox SFF """ . . "es suborganización de"@es . _:N7de514b998ce4a01a791171c2138f25b "Oxford" . . . . _:N213e2abcf42149548c1cf3a5b8b57d47 . "52283448"^^ . """Job Description _________________________________________________________________________ Summary Job title Training Director, Schmidt AI in Science Africa-India-Oxford Faculty Fellowship Programme Division MPLS Department Doctoral Training Centre Location 1-4 Keble Road, Oxford OX1 3NP and remote Grade and salary Grade 8: £48,235-£57,255per annum (expected) Hours Part time 0.5FTE Contract type Fixed-term for 3 years, with the possibility of extension Reporting to Directorate of Oxford’s Schmidt AI in Science Programme (David Gavaghan, Stephen Roberts, Ben Lambert) Vacancy reference Additional information The role The Africa-India-Oxford AI in Science Faculty Fellowship (AI2-Ox SFF) Programme is an exciting and innovative new research fellowship for early faculty from research institutes in resource -limited settings in Africa and India wishing to use AI to accelerate progress in other scientific fields. This programme is funded by a generous £5.5m donation from Schmidt Sciences, which builds on the success of Oxford University’s existing Eric and Wendy Schmidt AI in Science programme. This programme will provide funding for 18 Fellows, undertaking three -year Fellowships over the next five years. The Fellowship programme is housed in the University’s Mathematical, Physical and Life Sciences (MPLS) Division at the Doctoral Training Centre. This new programme is a partnership between the Africa Oxford Initiative (AfOx), the Oxford India Centre for Sustainable Development (OICSD), the existing Oxford University Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Programme, and four of Oxford’s Colleges (Linacre, Mansfield, Reuben and Somerville). During their three-year Fellowships, each Fellow will be bought out of their teaching commitments at their home institutions for the first and third years. During these years, the Fellows will focus on achieving their research goals, supported by Oxford and the Training Director and Programme Manager of the AI2-Ox SFF Programme. During the first year, the Fellows will also travel to Oxford and undertake cohort-based training in Research Software Engineering. In their second year of the Fellowship, the Fellows will be resident in Oxford and will be hosted by an existing member of faculty in an MPLS department. Meeting the objectives of the AI2-Ox SFF Programme will require the recruitment of Fellows with outstanding research trajectories from Africa and India. To achieve this and to be able to adequately support our Fellows throughout their Fellowship, this programme will be delivered in partnership with AfOx and the OICSD, and the Training Director of the Programme will work closely with these institutes. AfOx is a cross-university initiative based at the University of Oxford with the aim of facilitating equitable and sustainable collaborations between researchers based at the University of Oxford and African universities and additionally increasing the number of African students pursuing postgraduate degrees in Oxford. Since its establishment in 2016, AfOx has f acilitated over 250 new collaborations between 70 departments within the University of Oxford and 120 African institutions ranging across 32 countries and built a network of over 3000 members. OICSD is a unique Oxford -India partnership created to advance research on the complex challenges and opportunities posed by sustainable development in India. It was established through a historic agreement between the Government of India and the University of Oxford in 2013 and is hosted at Somerville College. OICSD has three key objectives: bringing together different academic disciplines and approaches to address a core set of sustainable development challenges in India; developing future leaders by providing fully funded scholarships to talented Indian graduate stud ents who would not otherwise be able to study at Oxford, so that they can research the scientific, social, political, economic and legal dimensions of sustainability in the country; and seeking to translate academic research into policy -relevant actions and impacts as it engages with a broad audience in the UK and India. In 2023, OICSD completed ten successful years and has, to date, funded more than 70 graduate students. Although we anticipate that each Fellow will already have experience in applying some aspects of AI and ML within their own fields, to achieve their research goals each Fellow will require and be provided with an individually tailored training programme to meet AI, Machine Learning and software development needs both of their research programme and their career and professional development. As applications-focused scientists, each research Fellow is likely to enter the programme with direct experience in a relatively narrow range of ML and AI techniques. In providing appropriate, individualised training to each of the Fellows, we will develop a comprehensive programme of graduate-level courses/one-to-one tutorials across the range of AI and ML to allow each fellow to extend their knowledge as their research programme unfolds. We will also provide extensive training and support from professional research software engineers with expertise in ML and AI to allow Fellows to implement both existing methods and any new methods that they develop in a robust, sustainable, and reusable manner. The Training Director of the programme will take primary responsibility for the development of this training programme and in supporting each Fellow in tailoring the overall progr amme to their individual career development needs and to the needs of their specific research project. The training programme itself will be built on and delivered by established and proven Centres for Doctoral Training, notably in Autonomous Intelligent Machines and Systems (AIMS), Sustainable Approaches to Biomedical Science: Responsible & Reproducible Research (SABS), Modern Statistics and Statistical ML (StatML), Intelligent Earth, and Health Data Science and will be held at the Doctoral Training Centre. The Training Director will contribute to this teaching in their own area of expertise. In addition, the Training Director will oversee: the procurement of any necessary new training modules and tailoring of existing modules to the needs of the programme; coordination of research software engineering training and support; the mentorship programmes for the Fellows; networking, peer -support and cohortdevelopment activities for the Fellows; and the equality, diversity and inclusion goals of the programme. Th ey will also participate in all academic-related components of the recruitment of fellows, which will likely involve sitting on recruitment panels. The Training Director will be a key point of contact for other related Schmidt Programmes within the UK and will play an important role in liaising with the funder (Schmidt Sciences). The University has committed substantial additional investment into the underpinning area of Research Software Engineering as part of its Schmidt Futures Programme, and the MPLS Division has identified the widespread December 2024 2 application of AI and machine learning techniques into the STEM sciences as a key strategic priority. The Training Director will be expected to play a leading role in the success of these broader initiatives, and in particular, will be expected to support major interdisciplinary funding initiatives put forward by the University. The Training Director will also be expected to play a key role in the planned development of Division -wide training provision in AI and ML. They will also be expected to support the activities of Oxford’s Schmidt AI in Science programme. In conducting their duties, the Training Director will have the direct support of the lead investigators (Professors David Gavaghan, Steve Roberts and Ben Lambert). The Training Director will be supported by a 0.75FTE Programme Administrator. Responsibilities Programme-related • • • • • • • • • • • • • • Lead the development and delivery of the academic training programme for the AI2 -Ox SFF Fellows in collaboration with the Directors of Oxford’s Schmidt AI in Science Programme, AfOx, OICSD and the Programme Administrator. Oversee the development and implementation of the training programme in software engineering for the AI2-Ox SFF Fellows, in collaboration with the Head of the Oxford Research Software Engineering Group. Establish a mentorship programme for the Fellows. Develop and support a comprehensive programme of networking, peer -support and cohort-development activities for the Fellows; this includes developing programmes for networking with the existing Schmidt AI in Science postdoctoral Fellows at Oxford and comparable Fellows funded by Schmidt Sciences at other research institutes. Develop and support a comprehensive programme of career and professional development activities including annual Career Development Reviews. Work with the host sponsor (based at Oxford), the Oxford College into which they are placed and their home institutions to ensure that Fellows’ training and research needs are being met. Support and enhance policies and processes to ensure that the equality, diversity and inclusion goals of the programme are met. Support all Fellows in the development of a responsible, reproducible and ethical approach to their research programme. Support all Fellows in developing an individual programme of research dissemination aimed at maximising the impact and utility of their work. Participate in the recruitment of Fellows, including possibly sitting on recruitment panels. Act as a point of contact for other Schmidt Science centres (in the UK and abroad) and play a key role in liaising with the funder (Schmidt Sciences); this includes travelling to meetings in the UK and abroad organised by the funder. Work with other members of the programme Directorate in seeking additional funding and support for the program, and in particular represent the programme in any large -scale strategic funding proposal put forward by the University in this area. Contribute to the development of Oxford’s existing Schmidt AI in Science programme. Contribute to the planned development of Division-wide training provision in AI and ML. To support your own research The activities that you will be expected to undertake to support the development of your own research, namely: • • • • Undertake your own research programme in an area of relevance to the Schmidt Sciences programmes at Oxford (that is, the application of AI and ML in the STEM sciences) and actively promote your research area. Initiate and implement long-term, often interdisciplinary research programmes in collaboration with appropriate groups across the university, nationally and internationally. Write funding applications for new projects and play a key role in establishing an overall research strategy. Develop new avenues of research, concepts and ideas to extend intellectual understanding. December 2024 3 • Regularly write research articles for international journals, book chapters, and reviews. Present papers at international conferences, and lead seminars to disseminate research findings. Selection criteria Essential selection criteria • • • • • • • • Hold a relevant PhD/DPhil with significant post-qualification research experience. Have a recognised research profile in the application of AI/ML within an applied scientific domain, commensurate with career stage. Have experience of Masters/PhD student supervision and/or post-doctoral researcher supervision commensurate with career stage. Have the ability to attract research funding and develop and maintain an independent research programme commensurate with career stage. Have teaching experience in higher education. Have interest in delivering graduate-level teaching in machine learning and/or AI. Have a demonstrable understanding of the current research landscape in terms of promoting a positive and inclusive research environment that values diversity and fosters equality. Be open-minded about other cultural norms and practices and be interested in learning about other cultures. Desirable selection criteria • • • • • Experience of cohort-based training (for example within a Centre for Doctoral Training or a postdoctoral Fellowship cohort or similar environment). Experience in directly interacting with funders and funding agencies. A track record of promoting equality and diversity initiatives in a higher education setting. Experience of supporting the professional and career development of early career research staff. Have demonstrable experience of current software development and software engineering practices as applied to AI and machine learning. 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. If you have previously worked for the University we will also verify key information such as your dates of employment and reason for leaving your previous role with the department/unit where you worked. 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 at: https://www.jobs.ox.ac.uk/pre-employment-checks 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 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 in dividual’s unique contribution. December 2024 4 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 www.ox.ac.uk/about/organisation. The Doctoral Training Centre The and The and DTC has been in existence since 2002 and has expanded and evolved according to the scientif ic f unding landscape. Originally admitting 20 DPhil students, the intake is now 90 - 100 per year. current programmes, of f ering 4-year interdisciplinary DPhil degrees to students of outstanding quality achievement are: • • • • • • BBSRC Interdisciplinary Bioscience Doctoral Training Partnership Sustainable Approaches to Biomedical Science Centre f or Doctoral Training UKRI AI Centre f or Doctoral Training in AI f or the Environment – Intelligent Earth NERC Environmental Research Doctoral Training Programme Interdisciplinary Lif e and Environmental Science Landscape Award programme Centre f or Doctoral Training (EIT CDT) in Fundamentals of AI For all of these, students are based within the Doctoral Training Centre building f or the f irst part of the programme, undertaking modular training courses to bridge the gaps in knowledge necessary to become successf ul research scientists bef ore embarking on the substantive research stage of the course within a host department of the University, at one of our collaborative institutions or embedded within one of our industrial partners f or years 2 – 4 of the course. In addition to DPhil training, the DTC also includes the Oxf ord Research Sof tware Engineering Group (OxRSE), which currently consists of 14 team members with f urther growth expected over the next 3 years. Over the past decade, an increasing number of academic researchers in all disciplines have come to rely on bespoke and reliable digital tools and sof tware in order to carry out their research. The OxRSE was established to provide essential research sof tware support. Working with research groups across the University, OxRSE creates, improves and maintains sof tware used f or world -class academic research and translational projects, and provides consulting and training on best practices in research sof tware development and reproducible research. OxRSE has recently been identif ied as a unit of strate gic importance within the University, with resources allocated to support rapid growth f rom the University’s Strategic Research Fund (SRF). This will see OxRSE recruit a substantially larger research support team, and begin a programme of systematic engagement with the wider university to gauge and meet research sof tware development needs The administration and f inances of the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship are held within the DTC, bringing post-doctoral training into our portf olio. This is an exciting and innovative new venture f or early career researchers wis hing to use AI to accelerate progress in other scientif ic f ields. It spans the interdisciplinary research of the departments primarily within the Mathematical, Physical and Lif e Sciences Division building a community of outstanding scientists (Fellows) with an excellent understanding of AI techniques and their application to scientif ic research and training them to become f uture research leaders. This £13M programme provides 110 post -doctoral years of f unding (around 50 individual Fellows) on one-, two-, or three-year f ellowships over six years. MPLS Division The Mathematical, Physical and Lif e Sciences (MPLS) Division is one of the f our academic divisions of the University. Oxf ord is widely recognised as one of the world’s leading science universities. The December 2024 5 disciplines within the MPLS Division regularly appear at the highest levels in world rankings and the REF 2021 results highlighted the quality of its research, the environment in which it is conducted and the impact it has. The MPLS Division is home to the non-medical sciences at Oxf ord and its 10 academic departments span the f ull spectrum on the mathematical, computational, physical, engineering and lif e sciences and undertake both f undamental research and cutting -edge applied work. Our research tackles major societal and technological challenges – whether developing new energy solutions or improved cancer treatments, understanding climate change processes, or helping to preserve biodiversity, and is increasingly f ocused on key interdisciplinary issues. We collaborate closely with colleagues in Oxf ord across the medical sciences, social sciences and humanities and with other universities, research organisations and industrial partners across the globe in pursuit of innovative research geared to address critical and f undamental scientif ic questions. MPLS is proud to be the home of some of the most creative and innovative scientif ic thinkers and leaders working in academia. Our senior researchers have been awarded some of the most signif icant scientif ic honours (including Nobel prizes and prestigious titles such as FRS and FREng) and we have a strong tradition of attracting and nurturing the very best early -career researchers who regularly secure prestigious f ellowships. The Division is also the proud holder of ten Athena Swan Awards (3 Silver and 7 Bronze) illustrating our commitment to ensure good practice and to encourage women in science at all levels in the division. We have around 6,000 f ull and part-time students (including approximately 2,000 graduate students) and play a major role in training the next generation of leading scientists. Oxf ord’s international reputation f or excellence in teaching is ref lected in its position at the top of the major league tables and subject assessments. MPLS academics educate students of high academic merit and potential f rom all over the world. Through a mixture of lectures, practical work and the distinctive college tutorial system , students develop their ability to solve major mathematical, scientif ic and engineering problems. MPLS is dedicated to bringing the wonder and potential of science to the attention of audiences f ar beyond the world of academia. We have a strong commitment to supporting public engagement in science through initiatives including Oxf ord Sparks portal (www.oxf ordsparks.net) and a large variety of outreach activities; these are crucial activities given so many societal and technological issues demand an understanding of the science that underpins them. We also endeavour to bring the potential of our scientif ic ef f orts f orward f or practical and benef icial application to the real world and our desire is to link our best scientif ic minds with industry and policy makers. For more inf ormation about the MPLS Division, please visit: www.mpls.ox.ac.uk December 2024 6 How to apply Applications are made through our online recruitment portal. Information about how to apply is available on our Jobs website https://www.jobs.ox.ac.uk/how-to-apply. 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 all documents 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. If you currently work for the University please note that: - as part of the referencing process, we will contact your current department to confirm basic employment details including reason for leaving although employees may hold multiple part-time posts, they may not hold more than the equivalent of a full time post. If you are offered this post, and accepting it would take you over the equivalent of full time hours, you will be expected to resign from, or reduce hours in, your other posts(s) before starting work in the new post. 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 ill-health/disability. Priority candidates are issued with a redeployment letter by their employing department(s). 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 Application FAQs, including technical troubleshooting advice is available at: https://staff.web.ox.ac.uk/recruitment-support-faqs Non-technical questions about this job should be addressed to the recruiting department directly: Samantha.taylor@dtc.ox.ac.uk. To return to the online application at any stage, please go to: www.recruit.ox.ac.uk. Please note that you will receive an automated email from our online recruitment portal to confirm receipt of your application. Please check your spam/junk mail if you do not receive this email. December 2024 7 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 at: https://compliance.admin.ox.ac.uk/job-applicant-privacypolicy. The University’s Policy on Data Protection is available at: https://compliance.admin.ox.ac.uk/dataprotection-policy. 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 of 30 September before the 70 th 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. December 2024 8 Benefits of working at the University Employee benefits University employees enjoy 38 days’ paid holiday, generous pension schemes, flexible working options, travel discounts including salary sacrifice schemes for bicycles and electric cars and other discounts. Staff can access a huge range of personal and professional development opportunities. See https://hr.admin.ox.ac.uk/staff-benefits Employee Assistance Programme As part of our wellbeing offering staff get free access to Health Assured, a confidential employee assistance programme, available 24/7 for 365 days a year. Find out more https://staff.admin.ox.ac.uk/health-assured-eap University Club and sports facilities Membership of the University Club is free for University staff. It 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. See www.club.ox.ac.uk and https://www.sport.ox.ac.uk/. Information for staff new to Oxford If you are relocating to Oxfordshire from overseas or elsewhere in the UK, the University's Welcome Service includes practical information about settling in the area, including advice on relocation, accommodation, and local schools. See https://welcome.ox.ac.uk/ There is also a visa loan scheme to cover the costs of UK visa applications for staff and their depend ants. See https://staffimmigration.admin.ox .ac.uk/visa-loan-scheme Family-friendly benefits We are a family-friendly employer with one of the most generous family leave schemes in the Higher Education sector (see https://hr.web.ox.ac.uk/family-leave). Our Childcare Services team provides guidance and support on childcare provision, and offers a range of high-quality childcare options at affordable prices for staff. In addition to 5 University nurseries, we partner with a number of local providers to offer in excess of 450 full time nursery places to our staff. Eligible parents are able to pay for childcare through salary sacrifice, further reducing costs. See https://childcare.admin.ox.ac.uk/. Supporting disability and health-related issues (inc menopause) We are committed to supporting members of staff with disabilities or long-term health conditions, including those experiencing negative effects of menopause. Information about the University’s Staff Disability Advisor, is at https://edu.admin.ox.ac.uk/disability-support. For information about how we support those going through menopause see https://hr.admin.ox.ac.uk/menopause-guidance Staff networks The University has a number of staff networks including for research staff, BME staff, LGBT+ staff, disabled staff network and those going through menopause. Find out more at https://edu.admin.ox.ac.uk/networks The University of Oxford Newcomers' Club The University of Oxford Newcomers' Club is 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. See www.newcomers.ox.ac.uk. Research staff The Researcher Hub supports all researchers on fixed-term contracts. They aim to help you settle in comfortably, make connections, grow as a person, extend your research expertise and approach your next career step with confidence. Find out more https://www.ox.ac.uk/research/support-researchers/researcher-hub December 2024 9 Oxford’s Research Staff Society is a collective voice for our researchers. They also organise social and professional networking activities for researchers. Find out more https://www.ox.ac.uk/research/supportresearchers/connecting-other-researchers/oxford-research-staff-society December 2024 10 """^^ . . . "170"^^ . . . "Document" . . "a un site"@fr . "ha sede"@it . . "51.75953"^^ . . . . . "site principal"@fr . . "Agent" . "Source"@en . . . . . _:N7de514b998ce4a01a791171c2138f25b "1 Keble Road" . "building" . "-1.259184"^^ . . . . . . . "logo" . . . _:N2727cab08d2f4740a5b62d7f3d81f2c4 "OX1 2JD" . "tiene sede en"@es . _:N7de514b998ce4a01a791171c2138f25b . . "OxPoints"@en . . . . _:N2727cab08d2f4740a5b62d7f3d81f2c4 . "application/rdf+xml" . . . "1-4 Keble Road" . . . . . . . . . . . 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