MARS Senior Research Associate - 0555-25

Lancaster University; Lancaster; On-site; GBP 40,000 - 50,000; Full time

Job summary

A leading research institution in Lancaster is seeking a Senior Research Associate to lead innovative research projects at the intersection of mathematics and AI. Candidates should hold a PhD in a relevant field and demonstrate research experience in applying mathematical methods. The position offers flexible working arrangements with a collaborative environment.

Benefits

Flexible working arrangements

Collaborative research culture

Participation in conferences

Qualifications

• Demonstrated experience in using mathematical methods to solve problems.
• Willing to participate in conferences and build research networks.
• Ability to work independently and collaboratively.

Responsibilities

• Lead a three-year research project oriented towards real-world applications.
• Contribute to collaborations with industry and academic partners.
• Engage in national and international research activities.

Skills

Research experience in Machine Learning

Ability to propose innovative research projects

Interpersonal skills

Publications record

Education

PhD in mathematics or related discipline

Job description

Social network you want to login/join with:

MARS Senior Research Associate - 0555-25, Lancaster

col-narrow-left

Client:

Lancaster University

Location:

Lancaster, United Kingdom

Job Category:

Other

-

EU work permit required:

Yes

col-narrow-right

Job Reference:

0726ac05b22d

Job Views:

13

Posted:

12.08.2025

Expiry Date:

26.09.2025

col-wide

Job Description:

Reference:

0555-25

Reference:

0555-25

The at Lancaster University is seeking to appoint Senior Research Associates to lead their own research project as part of‘.

MARS, which is funded by a £13m investment from Research England, conducts research and teaching at the interface of dynamical mathematical modelling and artificial intelligence (AI), with a focus on using applied mathematics and AI methods to address real-world challenges.

What we’re looking for

You will hold a PhD in mathematics or a related discipline and be able to demonstrate previous research experience inusing mathematical Machine Learning and AI methods, or applied mathematics, to solve challenging problems. Your research will have potential for real-world application in areas including, but not limited to, cyber security, engineering, environment and health.

You will be able to propose an innovative and deliverable three-year research project that contains substantial mathematical content and aligns with MARS research goals. You may also be asked to contribute up to 0.2 FTE to industry projects relevant to your expertise.

You will have a publications record appropriate to your career stage, which includes evidence of the ability to produce high-quality academic writing, and the potential to publish research with a substantial mathematical component in leading peer-reviewed journals and conferences.

Willingness to participate in national and international meetings, conferences and workshops to present results to a wider audience and build research networks is essential. You must also be prepared to build collaborations with MARS project partners and other non-academic stakeholders by attending and contributing to meetings and events.

You will have effective interpersonal skills and be able to work both independently and within a team. You will also be willing to contribute to developing a positive, inclusive and collaborative research culture within MARS.

Why join MARS?

It is an exciting time to be part of MARS, which is based in one of the top-ranked maths departments in the UK. You’ll be part of a thriving and collegiate research group with a growing complement of academic staff, researchers and PhD students. MARS is at the forefront of innovating mathematics and AI research and is a nationally distinctive group to join if you want to be part of the next generation of mathematicians tackling real-world problems and shaping the future of mathematics and AI.

For more information about MARS research visit our webpages .

These are full-time, three-year positions. Flexible working arrangements will be considered but you will be expected to be present on the Lancaster campus a minimum of two days a week.

Candidates who are considering making an application are strongly encouraged to contact the Head of MARS, Professor Chris Jewell or Professor Chris Nemeth to discuss the MARS programme in greater detail.

Lancaster University promotes equality of opportunity and diversity within the workplace. For these positions, we welcome applications from all diversity groups but particularly from women who are currently underrepresented in the mathematical sciences.

As part of the application process please click on the following link and complete this:

Further Details:

Please note: unless specified otherwise in the advert, all advertised roles are UK based.

Find out what it's like to , including information on our wide range of employee benefits, support networks and our policies and facilities for a family-friendly workplace.

The University recognises and celebrates good employment practice undertaken to address all inequality in higher education whilst promoting the importance and wellbeing for all our colleagues.

We warmly welcome applicants from all sections of the community regardless of their age, religion, gender identity or expression, race, disability or sexual orientation, and are committed to promoting diversity, and equality of opportunity.

#divSocialMedia { padding:10px 0; overflow:hidden; } #divSocialMedia span { margin-right:5px; } #divSocialMedia div { display:inline-block; margin:10px 5px; } #divSocialMedia a { font-size:1.5rem; font-family:sans-serif; border:1px solid #888; border-radius:50%; padding:8px; } #divSocialMedia i { font-size:1.5rem; } #divSocialMedia a:focus { outline-offset:2px; } let socialMediaClipboardId = -1; function socialMediaClipboard(lnk) { let url = lnk.getAttribute("data-url"); if (!navigator.clipboard) { fallBack(); } else { navigator.clipboard.writeText(url).then(success, fallBack); } function fallBack() { let ta = document.createElement("textarea"); ta.textContent = url; document.body.appendChild(ta); ta.select(); try { document.execCommand("copy"); document.body.removeChild(ta); success(); } catch (ex) { document.body.removeChild(ta); alert("Sorry, it is not possible to copy the advert link to your clipboard"); } } function success() { if (typeof lnk.origTitle == "undefined") lnk.originalTitle = lnk.title; lnk.title = lnk.getAttribute("data-succtitle"); let orig = lnk.getAttribute("data-origicon"), succ = lnk.getAttribute("data-succicon"); let i = lnk.getElementsByTagName("i")[0]; i.classList.remove(orig); i.classList.add(succ); clearTimeout(socialMediaClipboardId); socialMediaClipboardId = setTimeout(function () { lnk.title = lnk.originalTitle; i.classList.remove(succ); i.classList.add(orig); }, 4000); } return false; } Share: