Algorithm Developer (KTP Associate) (25001803)

Durham University; Chilton; On-site; GBP 30,000 - 40,000; Full time

Job summary

A prestigious academic institution seeks a KTP Associate to lead a project with MIRICO, focused on developing algorithms for enhancing gas emission localization and quantification. Ideal candidates will have a PhD in applied mathematics or related fields, alongside experience in scientific modelling with Python. This opportunity promises collaborative work, contributing to vital environmental solutions and innovation in gas measurement technologies.

Qualifications

• PhD or equivalent in applied mathematics, statistics, or related field.
• Minimum 2 years of experience in scientific or statistical modelling.
• Experience in developing scientific solutions in Python.

Responsibilities

• Lead a KTP project collaborating with MIRICO.
• Develop algorithms for gas emission localisation and quantification.
• Validate models against experimental data and refine.

Skills

Autonomous work

Team cooperation

Problem-solving skills

Novel idea application

Education

PhD in applied mathematics or related subject

Tools

Python

CFD modelling software

SQL

Job description

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. Diversity brings strength and we welcome applications from across the international, national and regional communities that we work with and serve.

The KTP Associate will lead a Knowledge Transfer Partnership (KTP) project that is a collaboration between Durham University and MIRICO, based in Oxfordshire. The Knowledge Transfer Partnership (KTP) scheme helps businesses to innovate and grow through the aid of discipline specific academic expertise. It does this by linking them with an academic supervisory team and a KTP Associate in a university to work on a specific project. Working alongside the Digital Team at MIRICO, the Algorithm developer will develop a new algorithm to enhance the localisation and quantification of gas emissions. This will involve leveraging advanced gas transport models, including advection-diffusion equations, computational fluid dynamics (CFD), and Navier-Stokes equations, to provide deeper insights into emission sources and dispersion patterns.

Key responsibilities

• Develop an algorithm for gas emission localisation and quantification using advection-diffusion models, CFD, and Navier-Stokes equations.
• 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.
• Carry out research at the highest standard and publish at conferences and journals.
• The results of the work will be embedded in MIRICO's solutions and directly contribute to driving innovation in gas emission monitoring.

Qualifications

Essential

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

Desirable

• 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

Essential

• 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.

Desirable

• 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.

Durham University is one of the world's top universities with strengths across the Arts and Humanities, Sciences and Social Sciences. We are home to some of the most talented scholars and researchers from around the world who are tackling global issues and making a difference to people's lives. Mirico (www.mirico.com) is an innovative precision gas measurement company based in Oxfordshire, leveraging unique technology originally developed by RALSpace. We provide state-of-the‑art laser spectroscopy solutions to accurately quantify and localise greenhouse gas emissions over large open areas enabling organisations to achieve their net‑zero climate goals. Our sensor products generate large volumes of data as they scan the environment for emissions 24 hours‑per‑day, 7 days a week. The measurements are processed on‑board the instrument before transmission to our cloud analysis platform which leverages custom atmospheric modelling, transforming raw measurements into detailed emissions information. Mirico believes the first step to reducing greenhouse gas emissions is to quantify them. We are working with a range of research and commercial organisations to prove, develop and perfect our technologies. We are a small, fast‑paced team integrating unique hardware and software in a friendly, collaborative environment.