Algorithm Developer (KTP Associate)

Durham University; North East; Hybrid; GBP 30,000 - 45,000; Full time

Job summary

A prestigious UK university is seeking an Algorithm Developer (KTP Associate) for a 18-month fixed-term position. The successful candidate will work with Mirico on developing algorithms for greenhouse gas emission quantification. Responsibilities include integrating sensor data, developing numerical methods, and collaborating with both university and corporate teams. Applicants should hold a PhD in applied mathematics and have experience in scientific modelling with Python. This role offers the opportunity to contribute to innovative environmental solutions.

Benefits

Support for professional development

Inclusive work environment

Access to innovative projects

Qualifications

• PhD or equivalent in applied mathematics or related field.
• Experience in scientific or statistical modelling, especially in commercial settings.
• Familiarity with Bayesian techniques and algorithm optimisation.

Responsibilities

• Integrate sensor data with gas transport models.
• Develop numerical methods for prediction accuracy.
• Collaborate with Mirico's Digital Team.

Skills

Python programming

Scientific modelling

Data processing

Problem-solving

Collaboration

Education

PhD in applied mathematics or related subject

Tools

SQL

Postgres

Python visualisation libraries

Job description

We welcome applications from candidates with disabilities, neurodiversity and long-term health conditions, and we are committed to ensuring fair treatment throughout the recruitment process.

We will make adjustments to support the recruitment and interview process wherever it is reasonable to do so and, where successful, adjustments will be made to support people within their role.

If you are unable to complete your application via our recruitment system or would like to discuss any reasonable adjustments to support you in the application process, please get in touch with us at [e-mail].

Algorithm Developer (KTP Associate)

Job Number: 25001803

Department: Department of Mathematical Sciences

Contract: Fixed Term – Full Time (18 months)

Closing Date: 12-Jan-2026, 11:59:00 PM

Durham University seeks to promote and maintain an inclusive and supportive environment for work and study that assists all members of our University community to reach their full potential. We welcome applications from across international, national and regional communities.

Mirico (www.mirico.com) is an innovative precision gas measurement company based in Oxfordshire. Our sensor products generate large volumes of data to quantify and localise greenhouse gas emissions, enabling organisations to achieve their net‑zero climate goals.

The KTP Project

The KTP Associate will lead a Knowledge Transfer Partnership between Durham University and Mirico, based in Oxfordshire. You will work alongside the Digital Team at Mirico to develop a new algorithm that enhances localisation and quantification of gas emissions, using advanced gas transport models, including advection-diffusion equations, computational fluid dynamics (CFD), and Navier-Stokes equations.

Specific Responsibilities

Successful applicants will need to be in post before 01/03/2026, with an earlier start date possible.

• Integrate sensor data with gas transport models for improved detection.
• Develop numerical methods to enhance prediction accuracy.
• Collaborate with Mirico’s Digital Team to optimise performance.
• Validate models against experimental data and refine as needed.

The candidate is expected to carry out research at the highest standard and will be supported to publish at conferences and journals. The results of the work will be embedded in Mirico’s solutions and directly contribute to innovation in gas emission monitoring.

Person Specification

Qualifications

• A good first degree and a PhD (or equivalent) in applied mathematics, statistics or a related subject.

Experience

• Actively involved in at least one project that delivered specific outcomes into a commercial organisation.
• Minimum 2 years academic and/or commercial experience of scientific or statistical modelling.
• Developing scientific solutions in Python, including selection and use of libraries.
• Processing large data sets, data pipelines, algorithm optimisation.
• Computational Fluid Dynamics (CFD) modelling and simulations.
• Presenting scientific findings to technical and non‑technical audiences.
• Formal academic and report writing of a quality commensurate with higher education qualifications.
• Collaboration projects with academic/industry colleagues for software development.
• Producing research publications in journals and conferences.
• Familiarity with Agile teams and processes.
• Presenting research findings at national/international venues.
• Advanced gas transport modelling, particularly for environmental simulations, gas dispersion, or emissions forecasting.

Skills

• Ability to work autonomously, organising and planning own workload against the project plan, with excellent time‑management skills.
• Demonstrable ability to work cooperatively as part of a team.
• Demonstrable problem‑solving skills.
• Ability to propose and apply novel (literature‑based) and innovative ideas for solving a problem.
• Knowledge of Bayesian uncertainty techniques, including emulation, history matching or equivalent calibration techniques.
• Ability to attract collaboration and opportunities for the project.
• Ability to plan and manage independent research.
• Knowledge of Python visualisation libraries – Bokeh, Holoviews.
• SQL, Postgres and SQLAlchemy.
• Familiarity with software process – coding standards, unit tests and source control.

Reporting and Location

Responsible to: Dr Andrew Iskauskas, Willmore Fellow, Department of Mathematical Sciences, Durham University.

Dr Jason Schmidberger, Senior Data Scientist, Mirico.

The KTP Associate will be employed by Durham University but will be based at Mirico, Harwell Campus, Oxfordshire, and will be expected to spend time in Durham University to undertake the partnership’s objectives.

Additional Information

For an informal discussion about the post please contact the recruitment team. We welcome applications from candidates with disabilities, neurodiversity and long‑term health conditions, and we are committed to ensuring fair treatment throughout the recruitment process.