Lecturer in Numerical Analysis & Data Science
About the role
The Department of Mathematical Sciences at the University of Bath is looking to appoint a Lecturer in Numerical Analysis & Data Science. The appointee will strengthen our research in computational mathematics and data science and contribute to our growing teaching portfolio in these areas.
About us
The Department of Mathematical Sciences has over 75 academic staff from all areas of Mathematics. There are strong interactions between Probability, Numerical Analysis and Applied Mathematics, as well as a wide variety of interdisciplinary research projects and industrial collaborations.
Members of the Numerical Analysis & Data Science group have an important supporting role in the research culture of the department’s EPSRC centre for doctoral training, SAMBa (Statistical Applied Mathematics at Bath), which has an annual intake of 10-15 research students. See https://samba.ac.uk/. Our department currently holds an Athena SWAN Gold Award.
About you
- Research: You will develop an independent, internationally recognised research programme that applies rigorous mathematics to problems in computational and data science. It will complement existing strengths in the department, such as numerical linear algebra, stochastic methods, machine learning, mathematical imaging, differential equations, optimisation, and inverse problems.
- Collaboration: You will work with one or more of our research groups and centres, including the Numerical Analysis group and the Centre for AI. Through the Institute for Mathematical Innovation (IMI), you will have the opportunity to build industrial and interdisciplinary partnerships.
- Funding and impact: You will be expected to develop and submit competitive applications for external research funding and to take part in knowledge exchange and impact activities.
- Teaching: You will teach at undergraduate and postgraduate level, including on our BSc in Mathematics, Statistics and Data Science and our MSc programmes in Statistics and Data Science. You will supervise PhD students, including through our EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa).
You will also take a full part in the life of the department, taking on administrative and management roles suited to the post.
Further information
This is a full time (36.5 hours per week) position.
Applications from all groups currently under-represented in academic posts are particularly encouraged. We are working to improve the present gender balance within the department, and particularly welcome applications from women. The Department and the University are committed to providing a supportive and inclusive working environment. Flexible working options will be considered wherever possible. For more information, https://www.bath.ac.uk/publications/flexible-working-policy/.
For an informal discussion regarding the role, please contact Tim Rogers at ma3tcr@bath.ac.uk or Jennifer Tweedy at jht55@bath.ac.uk.
We consider ourselves to be a university where difference is celebrated, respected and encouraged. We have an excellent international reputation with staff from over 60 different nations and have made a positive commitment towards gender equity and intersectionality receiving a Silver Athena SWAN award. We truly believe that diversity of experience, perspectives, and backgrounds will lead to a better environment for our employees and students and encourage applications from all genders, backgrounds, and communities, particularly from under-represented groups, and value the positive impact that will have on the university. We are committed to maintaining a safe and secure environment for our students, staff, and community by reinforcing our Safer Recruitment commitment.
We're very proud to be a signatory of the Armed Forces Covenant. an accredited Disability Confident Leader; autism friendly university, committed to building disability confidence and supporting disabled staff.
What we can offer you
We're continually expanding our benefits package to better support you and enhance your experience with us and the below is just an example of some of the many great benefits we offer:
- Generous annual leave allowance with an additional 5 discretionary days so that you can enjoy a positive work life balance
- Generous employer contributory pension schemes
- Cycle to work scheme
- Electric vehicle salary sacrifice scheme
- Staff discount at Team Bath gym
- Staff benefits include discounted postgraduate tuition and language courses, alongside a wide range of personal and professional development opportunities such as apprenticeships, LinkedIn Learning, and more
- Local discounts, including free entry to the Holburne Museum in Bath
- A family-friendly workplace
- An excellent reward package that recognises the talents of our diverse workforce
- Relocation allowance
- Visa reimbursement and Interest-Free Loan to help with the cost of some immigration expenses
- Employee assistance services through Health Assured, including access to the Wisdom app
Find out more about our benefits and watch the video to hear from our staff about what makes the University of Bath a great place to work as well as following us X and LinkedIn.
Be Well at Bath
We’re committed to creating a health-supporting working environment where everyone can thrive and be at their best. We offer a range of resources to enable you to do that from your first day here, including:
- Staff support groups and networks
- A network of Staff Wellbeing Champions
- A suite of tools, resources and frameworks that enable you to be at your best and thrive
Find out more about being at your best at Bath.
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Further details:
Terms and Conditions of Employment
Right to Work in the UK: We do not assess immigration or right to work status until offer stage. Being invited to interview does not guarantee you are eligible for visa sponsorship and all offers are conditional on meeting right to work requirements. Further information is available on our application support webpage.
Anonymous shortlisting: We are constantly seeking to reduce the unconscious bias that enters any assessment process, with the goal of creating an inclusive and equal assessment process. To support this, personal details such as your name, may be removed from application forms at the initial shortlisting stage.