Senior Research Associate - MARS

The School of Mathematical Sciences at Lancaster University is inviting applications for the position of Senior Research Associate, a pivotal role within the exciting new initiative, 'MARS: Mathematics for AI in Real-world Systems'. This program, bolstered by a significant £13m investment from Research England, sits at the vanguard of research and teaching, expertly blending dynamical mathematical modelling with cutting-edge Artificial Intelligence (AI). The core mission of MARS is to leverage applied mathematics and AI methodologies to tackle pressing real-world challenges across diverse sectors.

This opportunity is ideal for ambitious researchers looking to lead their own innovative three-year project. Successful candidates will possess a PhD in mathematics or a closely related field, coupled with a demonstrable track record in applying mathematical machine learning, AI methods, or advanced applied mathematics to complex problems. The potential for real-world impact in areas such as cyber security, engineering, environmental science, and health is a key consideration for project proposals.

Advantages for Potential Candidates:

• Lead Your Own Research: This role offers the unique advantage of conceptualizing and leading an independent, three-year research project. This is a fantastic platform to drive your research agenda and make a significant contribution to the field.
• Interdisciplinary Impact: MARS is explicitly focused on translating academic research into tangible, real-world applications. If you are passionate about seeing your mathematical and AI innovations make a difference, this is the place for you.
• Thriving Research Environment: Become part of one of the UK's top-ranked mathematics departments, situated within a vibrant and collegial research group. You will collaborate with a growing team of academics, researchers, and PhD students, fostering a dynamic and supportive atmosphere.
• Cutting-Edge AI and Mathematics: MARS is at the forefront of innovation at the intersection of mathematics and AI. This is an opportunity to shape the future of these fields and be recognized as a key player in next-generation mathematical research.
• Career Progression: As a Senior Research Associate, you will gain invaluable experience in research leadership, project management, and interdisciplinary collaboration, all of which are highly transferable skills that can significantly advance your career trajectory.
• Industry Engagement: The role may include contributing to industry projects (up to 0.2 FTE), providing practical experience and valuable networking opportunities within relevant commercial sectors.

Key Considerations for Your Application:

• Innovative Project Proposal: The cornerstone of your application will be a compelling proposal for a three-year research project. It must demonstrate substantial mathematical content and clearly align with the overarching goals of MARS. We encourage you to carefully review the guidance provided for this proposal.
• Research Experience: Strong evidence of prior research experience in mathematical machine learning, AI, or applied mathematics, particularly in solving challenging problems with potential real-world applications, is essential.
• Commitment to Campus Presence: While flexible working arrangements will be considered, candidates must be prepared to be present on the Lancaster campus for a minimum of two days per week.
• Diversity and Inclusion: Lancaster University is committed to fostering equality and diversity. Applications from all backgrounds are welcomed, with a particular encouragement for women, who are currently underrepresented in the mathematical sciences.
• Application Requirements: Ensure you submit all mandatory attachments as PDFs, including your research proposal, a cover letter, and your full academic CV.

This is a full-time, three-year position. Interviews are scheduled to take place on Monday 9th and Tuesday 10th February. For those considering an application, we strongly encourage you to reach out to the MARS programme leads to discuss the opportunity in more detail.