Job Purpose

To make a leading contribution to the development of innovative muon tracking algorithms for cutting-edge applied nuclear physics research. The successful candidate will be expected to contribute towards the STFC Late-Stage Commercialisation project “Natural NDT-CE” under PI Dr David Mahon.  The candidate is also expected to support the wider experimental research programme of the Nuclear & Hadron Physics research group.

Main Duties and Responsibilities

Perform the following activities in conjunction with and under the guidance of the Principal Investigator:

1.       Take a leading role in the planning and conduct of assigned research individually or jointly in accordance with the project deliverables and Nuclear & Hadron Physics group research strategy.

2.       Lead the development of innovative particle identification and noise filtering algorithms based on Machine Learning techniques to improve the detection of muons in a variety of particle detector systems.

3.       Lead the development muon tracking algorithms based on Machine Learning techniques.

4.       Lead the development of streaming data acquisition software for close to real time muon event processing and rejection of superfluous data.

5.       Survey current solutions and research literature to understand the research challenges associated with the project and the wider need of the Nuclear & Hadron Physics Research Group.

6.       Play a leading role in the group’s research and development into Machine Learning analytical techniques for a range of uses including detector readout and triggering systems.

7.       Support the integration of data acquisition and processing software into experimental muon imaging systems.

8.       Establish and maintain your research profile and reputation and that of University of Glasgow, School of Physics & Astronomy and Nuclear & Hadron Physics Research Group, including establishing and sustaining a track record of independent and joint publications of international quality in high profile/quality refereed journals, enhancing the research impact in terms of economic/societal benefit, and gathering indicators of esteem.

9.       Documentation of research and development in appropriate technical documents.

10.    Presentation of work at international and national collaboration meetings, conferences, internal and external seminars, colloquia and workshops to develop and enhance our research profile.

11.    Take a leading role in developing and maintaining collaborations with colleagues across the Nuclear & Hadron Physics Research Group, School of Physics & Astronomy, College of Science & Engineering, the University of Glasgow and wider community (e.g. Academic and Industrial Partners).

12.    Play a supporting role in the research and development undertaken by postgraduate students and nuclear technicians to ensure their effective development.

13.    Keep up to date with current knowledge and recent advances in the field/discipline.

14.    Engage in personal, professional and career development, to enhance both specialist and transferable skills in accordance with desired career trajectory.

15.    Undertake any other reasonable duties as required by Project PI or Head of School.

16.    Contribute to the enhancement of the University’s international profile in line with the University’s Strategic Plan, World Changers Together

Knowledge, Qualifications, Skills and Experience

Knowledge & Qualifications

Essential:

A1 Normally Scottish Credit and Qualification Framework level 12 (PhD) plus track record of emerging independence within a research/professional environment, or alternatively possess professional qualifications and experience equivalent to PhD level plus the requisite experience.

A2 Specialist theoretical and practical knowledge of Machine Learning and charged particle tracking.

Desirable:

B1 An up-to-date knowledge of hadron physics and data analysis methods.

Skills

Essential:

C1 Project or subject specific skills.

C2 Research creativity and cross-discipline collaborative ability as appropriate.

C3 Excellent communication skills (oral and written), including public presentations and ability to communicate complex data/concepts clearly and concisely.

C4 Excellent interpersonal skills including team working and a collegiate approach.

C5 Appropriate workload/time/project/budget/people management skills

C6 Extensive IT and data analysis/interpretation skills as appropriate.

C7 Self-motivation, initiative and independent thought/working.

C8 Problem solving skills including a flexible and pragmatic approach.

C9 A comprehensive and up-to-date knowledge of current issues and future directions within the wider subject area or subject specialism.

C10 Knowledge of project specific technical models, equipment or techniques.

C11 Sufficient depth of relevant research experience, normally including sufficient postdoctoral experience in a related field, appropriate to an early career researcher.

Desirable: 

D1 Ability to develop simulations using the GEANT4 toolkit.

D2 Ability to develop high level analysis using ROOT analysis framework

D3 Comprehensive knowledge of Machine Learning frameworks such as PyTorch and TensorFlow.

Experience

Essential:

E1 Sufficient relevant research experience (or equivalent) appropriate to an early career researcher.

E2 Project or subject specific experience.

E3 Experience of conducting systematic reviews in relevant area.

E4 Experience of scientific writing.

E5 Proven ability to deliver quality outputs in a timely and efficient manner.

E6 Evidence of an emerging track record of publications in a relevant field.

E7 A track record of presentation and publication of research results in quality journals/conferences.

E8 Experience of making a leading contribution in academic activities.

E9 Ability to demonstrate a degree of independence as illustrated by identification of project objectives from assessment of the literature, design & analysis of experiments & drafting of papers.

E10 Experience in undertaking independent research.

E11 Experience with Machine Learning applied to particle tracking and noise rejection.

E12 Experience with streaming data acquisition techniques and real time analyses.

Desirable:

F1 Strong knowledge of the field of muography, its techniques and technologies.

Closing date:  4 September 2025

Terms and Conditions

Salary will be Grade 7, £41,064 - £46,049 per annum.

This post is full time, and has funding for up to 1 year from start date.

The University of Glasgow has a responsibility to ensure that all employees are eligible to live and work in the UK.  If you require a Skilled Worker visa to work in the UK, you will be required to meet the eligibility requirements of the visa route to be assigned a Certificate of Sponsorship.

Please note that this post may be eligible to be sponsored under the Skilled Worker visa route if tradeable points can be used under the Skilled Worker visa rules. For more information please visit: https://www.gov.uk/skilled-worker-visa.

As a valued member of our team, you can expect:

1 A warm welcoming and engaging organisational culture, where your talents are developed and nurtured, and success is celebrated and shared.

2 An excellent employment package with generous terms and conditions including 41 days of leave for full time staff, pension - pensions handbook https://www.gla.ac.uk/myglasgow/payandpensions/pensions/, benefits and discount packages.

3 A flexible approach to working.

4 A commitment to support your health and wellbeing, including a free 6-month UofG Sport membership for all new staff joining the University  https://www.gla.ac.uk/myglasgow/staff/healthwellbeing/.

We believe that we can only reach our full potential through the talents of all. Equality, diversity and inclusion are at the heart of our values. Applications are particularly welcome from across our communities and in particular people from the Black, Asian and Minority Ethnic (BAME) community, and other protected characteristics who are under-represented within the University. Read more on how the University promotes and embeds all aspects of equality and diversity within our community https://www.gla.ac.uk/myglasgow/humanresources/equalitydiversity/.

We endorse the principles of Athena Swan https://www.gla.ac.uk/myglasgow/humanresources/equalitydiversity/athenaswan/ and hold bronze, silver and gold awards across the University.

We are investing in our organisation, and we will invest in you too. Please visit our website https://www.gla.ac.uk/explore/jobs/ for more information.