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- Tasks: Join Professor Malwina Luczak in cutting-edge research on Applied Probability and Markov chains.
- Company: Dynamic university department focused on innovative mathematical research.
- Benefits: Market-leading pension, health services, generous leave, and local discounts.
- Other info: Flexible working arrangements available to support work-life balance.
- Why this job: Make a real impact in mathematics while developing your own research agenda.
- Qualifications: Strong background in mathematics and research skills in applied probability.
The predicted salary is between 36000 - 60000 £ per year.
Applications are invited for the above post, to start in May 2026 for a fixed term of two years.
Research Focus
Work with Professor Malwina Luczak on projects in the field of Applied Probability connecting to her Leverhulme International Professorship. The research centres on Markov chains, rigorous analysis of their long‑term behaviour, adaptation of techniques to specific classes of Markov chains in application areas such as mathematical biology and computer science, and verification of theoretical results by numerical work.
Responsibilities
- Assist in adapting existing techniques to new classes of Markov chains.
- Conduct numerical work to verify theoretical results.
- Develop own research agenda within the area.
- Collaborate with colleagues in the Department of Mathematics.
Benefits
- Fantastic market leading Pension scheme
- Excellent employee health and wellbeing services including an Employee Assistance Programme
- Exceptional starting annual leave entitlement, plus bank holidays
- Additional paid closure over the Christmas period
- Local and national discounts at a range of major retailers
Recruitment Information
Applications should normally be made online. Attach a brief statement of motivation (maximum 2 sides A4, excluding references) to your CV, describing your research and how your interests and skills fit in with the project. Informal enquiries may be made to Professor Malwina Luczak (email: malwina.luczak@manchester.ac.uk). General enquiries: recruitmentservices.people@manchester.ac.uk.
The vacancy will close for applications at midnight on the closing date. The person specification criteria are in the Further Particulars document.
Equal Opportunity Statement
As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
Other Information
The Department and University are committed to the well‑being and work‑life balance of all staff. We have a package of family‑friendly policies covering flexible working, career breaks and entitlement to paid maternity, paternity and adoption leave. Full‑time post but part‑time or flexible arrangements welcome.
We are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies. Any recruitment enquiries from recruitment agencies should be directed to recruitmentservices.people@manchester.ac.uk. Any CV’s submitted by a recruitment agency will be considered a gift.
Research Associate in Applied Probability in Manchester employer: The University of Manchester
Contact Detail:
The University of Manchester Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Associate in Applied Probability in Manchester
✨Tip Number 1
Network like a pro! Reach out to current or former employees in the field of Applied Probability. A friendly chat can give us insights into the role and might even lead to a referral.
✨Tip Number 2
Prepare for an informal chat with Professor Malwina Luczak. Show genuine interest in her research and be ready to discuss how your skills align with her projects. This could set you apart from other candidates!
✨Tip Number 3
Don’t underestimate the power of a strong online presence. Update your LinkedIn profile to reflect your research interests and connect with professionals in the field. It’s a great way to get noticed!
✨Tip Number 4
Apply through our website! Make sure to attach that brief statement of motivation, highlighting your research agenda and how it fits with the role. We want to see your passion shine through!
We think you need these skills to ace Research Associate in Applied Probability in Manchester
Some tips for your application 🫡
Craft a Compelling Statement of Motivation: When writing your statement, make sure to highlight your research interests and how they align with Professor Malwina Luczak's projects. Keep it concise but impactful, showing us why you're the perfect fit for this role.
Tailor Your CV: Your CV should reflect your skills and experiences relevant to applied probability and Markov chains. We want to see how your background connects to the responsibilities outlined in the job description, so don’t hold back!
Follow the Application Guidelines: Make sure to apply through our website and stick to the specified format. Remember, we love a well-organised application, so keep everything neat and professional to make a great first impression.
Check Your Work: Before hitting that submit button, give your application a thorough proofread. Typos and errors can distract from your qualifications, and we want to see your best work. A polished application shows us you care!
How to prepare for a job interview at The University of Manchester
✨Know Your Research
Before the interview, dive deep into Professor Malwina Luczak's work and the specific projects related to Applied Probability. Familiarise yourself with Markov chains and their applications in mathematical biology and computer science. This will not only show your genuine interest but also help you engage in meaningful discussions during the interview.
✨Tailor Your Motivation Statement
Craft a compelling motivation statement that clearly outlines how your skills and research interests align with the position. Be specific about your previous experiences and how they relate to adapting techniques for new classes of Markov chains. This personal touch can make a significant difference in how you are perceived.
✨Prepare for Technical Questions
Expect technical questions related to your understanding of Markov chains and numerical verification methods. Brush up on relevant theories and be ready to discuss how you would approach specific problems. Practising with peers or mentors can help you articulate your thoughts clearly.
✨Show Collaborative Spirit
Since collaboration is key in this role, be prepared to discuss your experience working in teams. Share examples of how you've successfully collaborated with colleagues in the past, especially in research settings. Highlighting your ability to work well with others will resonate well with the interviewers.