MPLS Doctoral Training Centre, 1-4 Keble Road, Oxford
Description of Course Director, Intelligent Earth CDT
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177986 Job Description Course Director Intelligent Earth CDT
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We are seeking to recruit to the post of Course Director for the Intelligent Earth Centre for Doctoral Training (CDT) in AI for the Environment. As Course Director, you will use your research expertise in AI and/or quantitative environmental sciences, working closely with the Academic Director to advance and deliver the curriculum and training programme with academics across Oxford for this exciting and innovative CDT, training cohorts of around 20 doctoral students annually. Although the CDT is primarily based within the MPLS Doctoral Training Centre, it spans many different departments across the University and a broad portfolio of external partners, drawing on expertise and resources to provide a highly interdisciplinary student experience. It combines taught courses in environmental sciences, research projects, transferable professional skills training and research seminars with a focus on tackling some of the most pressing environmental issues using AI and ML. With the support of the Programme Manager, you will be responsible for the day to day running and monitoring of the training programme, ensuring that it is relevant, focused and fulfils the requirements of the students, academics, partners and funding body. This post provides the opportunity to contribute to teaching areas of the curriculum within your field of specialism and you 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 post-doctoral fellowships, subject to approval by the funding body and the department(s)/college where the fellowship is held. Information on the programme can be found here: https://intelligent-earth.ox.ac.uk/home. Applications for this vacancy are to be made online. You will be required to upload a CV and supporting statement as part of your online application and details of three referees. If you do not wish the University to contact your referees before being progressed to the shortlist stage, please answer the relevant reference questions accordingly. Only applications received before midday (UK time) on 24th February 2025 will be considered.
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Job Description __________________________________________ Summary Job title Course Director, Intelligent Earth CDT Division Mathematical, Physical and Life Sciences Division Department MPLS Doctoral Training Centre Location 1-4 Keble Road, Oxford Grade and salary Grade 8, £48,235 - £57,255 with a discretionary range to £62,407 per annum (pro rata) Hours Part time (50%FTE) Contract type Fixed term (3 years) Reporting to Academic Director, Intelligent Earth CDT Vacancy reference Additional information The role The Intelligent Earth UKRI AI Centre for Doctoral Training in AI for the Environment The University of Oxford Intelligent Earth UKRI AI Centre for Doctoral Training in AI for the Environment admits up to 20 funded students per year to a 4-year DPhil (PhD) programme. The CDT is hosted across seven departments: Physics, Biology, Computer Science, Earth Sciences, Engineering Science, Statistics, and the School of Geography and the Environment in the Mathematical, Physical and Life Sciences and Social Sciences divisions. Each cohort comprises around 20 doctoral students annually, with funding provided for five intakes. The aim of the CDT is to deliver targeted cohort-based training programme, equipping a new generation of PhD students to tackle some of the most pressing environmental issues using AI and ML through five closely connected themes: (1) Climate (2) Biodiversity (3) Natural hazards (4) Environmental solutions (5) Core AI/ML research. The programme is overseen by the Director, Professor Philip Stier. The Course Director is responsible for developing and helping to run the interdisciplinary training programme of the CDT, spanning across AI and environmental sciences, ensuring that it is relevant, focussed and meets the needs of the students and supervisors both in Oxford and from our partners. The Course Director also oversees the day-to-day academic delivery of the programme. The CDT delivers a targeted interdisciplinary cohort-based training programme with two entry streams, one for highly numerate candidates from environmental, physical and mathematical science backgrounds and the other for environmentally driven candidates from computer science, data science, statistics backgrounds. Critical to the delivery of a truly interdisciplinary cohort of doctoral students, the programme combines mandatory taught courses in environmental and data sciences, research projects, transferable skills training, and interdisciplinary research seminars, with the active involvement of our non-academic partners, as outlined in detail below. The teaching model for all courses is tailored towards training graduate students to become independent researchers with a high degree of transferable skills. For each course, after introductory lectures, students are introduced to the corresponding AI tools, frameworks (e.g., Tensorflow,…), and environmental datasets (provided in a cloud-based setting) to apply the taught material in tutorial-based project work. Students work in interdisciplinary groups tackling grand challenges in environmental science of increasing complexity with AI, supported by peer learning. Cross-cohort group work is accompanied by tutorials that are formally assessed. Together with other cohort building activities, such as our hackathons, this enables students to network and build a community. Core courses establish a “common language” between students with different backgrounds that is key to cohort building and unlocking interdisciplinary synergies. Identified training needs determine mandatory course selection from the CDT programme as well as from additional graduate courses available from a vast selection delivered across Oxford and its associated DTPs/CDTs. This allows students flexibility in co-designing their individual training plans, an aspect that has been recently identified as a key driver of student satisfaction in our doctoral programmes and supports their professional development. Structure of the teaching programme: • Year 1: First term: core courses in software engineering and environmental data analysis followed by responsible AI and foundational machine learning and environmental science courses. Second term: advanced ML courses with focus on environmental data and science questions. Third term: three-month research project followed by the annual hackathon and conference. Course free periods are used for consolidation, supervisor matching, and PhD proposal development (requested in CDT/DTP student feedback). • Year 2: Transition to host department(s) and supervisors. Start of PhD (Oxford: DPhil) research. Continued training based on training needs analysis. Annual hackathon & conference. Potential secondment with nonacademic partners (or in year 3). • Year 3: Focus on PhD research with optional advanced courses and professional skills training modules based on training needs analysis, followed by the annual conference and hackathon. Potential secondment with nonacademic partners (or in year 2). • Year 4: Finalisation of PhD research and thesis writing. Professional training focusing on career development, job/fellowship applications and interviews. In year 1, students also undertake a 3-month research project supervised by one of the potential PhD supervisors, chosen based on interest of the students and to consolidate taught material. Students are required to deliver a written report that will be formally assessed and presented to the cohort. The Intelligent Earth CDT is intrinsically interdisciplinary: each student project is advised by both an environmental science supervisor and an AI supervisor, plus their non-academic partner advisor, 2 who serve as host for a non-academic secondment. The primary department and supervisor are assigned based on the focus of the project and the background of the student, thus delivering a personalized training approach for each student, leveraging their individual strengths and interests. January 2025 2 Our institutional commitment to EDI is reflected by Oxford’s institutional Athena Swan Silver award as well as the Athena Swan awards held by all IE CDT departments. Responsibilities The key part of the role is to work with the Academic Director, Philip Stier, to advance, improve and deliver the curriculum and training programme, alongside contributing to the monitoring of student progress and welfare as part of the CDT core team. Intelligent Earth launched with the first cohort of students in autumn 2024 and delivered the first term of its training programme. Hence, the focus of this role is now on improvement and augmentation of the programme. There is also an administrative component to the role, working closely with the Programme Manager in this respect. The Course Director reports to the Academic Director and serves on the CDT Management Committee. This part time role 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 post-doctoral fellowships, subject to approval by the funding body and the department(s)/college where the fellowship is held. Duties include: • Augmentation and improvement of the Training Programme: Working closely with the Academic Director and academics across departments to develop an exciting (and coherent) curriculum for core and advanced training for the students from a wide range of quantitative backgrounds. • Teaching: Delivery of a proportion of the curriculum in line with the Course Director’s specialism. Administration • Admissions: Contributing to the CDT open days; assessment of applications; attending pre interview sift and post-interview decisions meetings. • Induction and cohort development: Contributing to the programme of activities to support cohortdevelopment. • Day to day monitoring of the training programme: Checking that the training programme meets expectations, and that modules are appropriate, coherent, relevant and delivered as expected. • Reporting: Contributing to termly and annual reporting – including the newsletter, and annual reporting to UKRI. • Networking: Supporting networking events with partners and other external agencies. Selection criteria Essential selection criteria • Research expertise in the areas of AI and/or quantitative environmental sciences • A Doctorate in a relevant discipline • Vision and drive to contribute to the development of an ambitious and exciting interdisciplinary training programme across AI and environmental sciences • A record of achievement in research with an appropriate track record of publications • Good organisational and motivational skills • Demonstrated interpersonal skills and the interest and ability to work as part of a dynamic Team January 2025 3 Desirable selection criteria • Experience of graduate mentoring • Familiarity with the use and development of digital learning tools • The ability to build good relationships with partners 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 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 www.ox.ac.uk/about/organisation. Doctoral Training Centre The DTC has been in existence since 2002 and has evolved and expanded to incorporate several Centres for Doctoral Training, offering 4-year interdisciplinary DPhil degrees to students of outstanding quality and achievement. The current programmes are:     BBSRC Interdisciplinary Biosciences Doctoral Training Partnership BBSRC iCASE Studentship Programme Chemistry in Cells DPhil Programme EIT CDT in Fundamentals of AI January 2025 4     EPSRC Sustainable Approaches to Biomedical Science Centre for Doctoral Training: Responsible and Reproducible Research ILESLA – Interdisciplinary Life and Environmental Science Landscape Award Intelligent Earth: UKRI AI Centre of Doctoral Training in AI for the Environment NERC Environmental Research Doctoral Training Partnership For all of these, students are based within the Doctoral Training Centre building for the first part of the programme. They undertake taught courses that bridge the gaps in knowledge necessary to become successful research scientists before embarking on the research stage of the course within a host partner department of the University, or at one of our collaborative institutions for years 2 – 4 of the course. In addition to DPhil training, the DTC also includes the Oxford Research Software Engineering Group (OxRSE), which currently consists of 17 team members with further 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 software in order to carry out their research. The OxRSE was established to provide essential research software support. Working with research groups across the University, OxRSE creates, improves and maintains software used for world-class academic research and translational projects, and provides consulting and training on best practices in research software development and reproducible research. OxRSE has recently been identified as a unit of strategic importance within the University, with resources allocated to support rapid growth from 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 software development needs The administration and finances of the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a program of Schmidt Futures, are held within the DTC, bringing post-doctoral training into our portfolio. This is an exciting and innovative new venture for early career researchers wishing to use AI to accelerate progress in other scientific fields. It spans the interdisciplinary research of the departments primarily within the Mathematical, Physical and Life Sciences Division building a community of outstanding scientists (Fellows) with an excellent understanding of AI techniques and their application to scientific research and training them to become future research leaders. This £13M programme provides 110 post-doctoral years of funding (around 50 individual Fellows) on one-, two-, or three-year fellowships over the next six years. The DTC is an extremely busy environment, with around 100 students admitted onto the programmes each year and approximately 35 members of academic and administrative staff. For more information, please visit: www.dtc.ox.ac.uk Mathematical, Physical, and Life Sciences Division Oxford is widely recognised as one of the world’s leading science universities for teaching, research and innovation. The Mathematical, Physical, and Life Sciences (MPLS) Division is one of the four academic divisions of the University, alongside the Humanities, Social Sciences and Medical Sciences Divisions. It is led by an academic Head of Division (Professor James Naismith) and an administrative Divisional Registrar (Dr Tracy Gale) and comprises nine of the University’s academic departments – Biology, Chemistry, Computer Science, Earth Sciences, Engineering Science, Materials, the Mathematical Institute, Physics, and Statistics – as well as Begbroke Science Park, the multidisciplinary Ineos Oxford Institute for Antimicrobial Research and an interdisciplinary Doctoral Training Centre. January 2025 5 MPLS is proud to be home to some of the most creative and innovative scientific thinkers and leaders in academia, whose interdisciplinary research is tackling major societal and technological challenges, from new energy solutions or improved cancer treatments to understanding climate change processes and helping to preserve biodiversity, tackling antimicrobial resistance, advancing AI and quantum technologies and space exploration, and much more. The quality and impact of our work have been recognised by successive rounds of the national Research Excellence Framework 5 and Teaching Excellence and Student Outcomes Framework exercises, and our departments frequently top the major higher education league tables. We teach around 7,300 students (including around 3,400 graduate students) and are playing a key part in training the next generation of leading scientists. Divisional activity is co-ordinated and represented by the MPLS Divisional Office based at 9 Parks Road, in the heart of Oxford’s Science Area. The Divisional Office, which is led by the Divisional Registrar, has around 55 dedicated members of staff, as well as a number of colleagues who are embedded in divisional teams but based in central University services (e.g. in Finance, HR and Development). To find out more, please visit: www.mpls.ox.ac.uk. Social Sciences Division The Social Sciences Division comprises fourteen departments: Anthropology and Museum Ethnography, School of Archaeology, School of Interdisciplinary Area Studies, Saïd Business School, Department of Economics, Department of Education, School of Geography and the Environment, Blavatnik School of Government, Department of International Development (Queen Elizabeth House), Oxford Internet Institute, Faculty of Law, Department of Politics and International Relations, Department of Social Policy and Intervention, Department of Sociology. The division has responsibility for over 700 academics in thirteen departments and the Faculty of Law, about 1740 graduate students, and 1900 undergraduates. It is also part of three cross divisional units: James Martin School, Oxford-Man Institute of Quantitative Finance and Smith School of Enterprise and the Environment. Each division has its own divisional secretariat, led by the Divisional Registrar. Each division is responsible for academic oversight of the teaching and research of its various departments and faculties, for strategic and operational planning, and for personnel and resource management. The divisional board and its principal committees undertake much of this. January 2025 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 three 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. January 2025 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/jobapplicant-privacy-policy. The University’s Policy on Data Protection is available at: https://compliance.admin.ox.ac.uk/data-protection-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 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. January 2025 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/staffbenefits 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-assuredeap 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 dependants. 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/researcherhub January 2025 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 January 2025 10