Simulation ML Specialist in Manchester, Greater Manchester, United Kingdom presso Arup

Job Title – Simulation ML Specialist

Location: Manchester / Birmingham / London

Joining Arup

Arup’s purpose, shared values and collaborative approach has set us apart for over 75 years, guiding how we shape a better world.

Our team (www.arup.com/dyna) supports Arup’s longstanding commitment to improve the world, by developing market-leading tools that enable us and our clients to develop solutions to tackle the most challenging engineering problems. Our Oasys LS-DYNA Environment software is used in the automotive, nuclear, and civil engineering community. One of its primary uses is the modelling and testing of vehicle crashworthiness, but it is also used to simulate design-critical scenarios in aerospace, seismic, nuclear, geotechnical, structural, and product design applications.

Watch this short clip to discover how Arup are shaping a better world and how you could be a part of it!Watch this short clip to discover how Arup are shaping a better world and how you could be a part of it!Watch this short clip to discover how Arup are shaping a better world and how you could be a part of it! 

The Opportunity

We currently have an exciting opportunity for a role in Scientific Machine Learning / Machine Learning for Simulations within our team.

The position offers an opportunity for applied research, software development, collaboration with engineering practitioners and with academia, and for managing and communicating our research activities. The post-holder is expected to work with a close-knit team that is geographically dispersed and diverse.

The post-holder will work closely with the product managers for solvers and for our engineering simulation products in addition to Arup domain experts. Reporting to the Associate Director of AI, they will be responsible for end-to-end research, implementation, and enhancement of new functionality in CAE software products. The area of work is initially within machine learning for engineering simulation within automotive design, however, in future this may expand to cover other advanced algorithms for engineering modelling and CAE workflows. In addition, the role also encompasses working with academic partners, communicating research to a variety of audiences, and identifying areas of strategic interest in alignment with the groups aims and goals.

You will perform the following duties on an ongoing basis:

• Work with the product management team to identify end-users’ modelling problems and abstracting them mathematically.

• Survey the relevant literature and understand the current state of the art in the field.

• Algorithm design, prototyping and peer review.

• Create pipelines to generate simulation datasets and leverage existing assets.

• Validate chosen implementation using an appropriate method, for example, through analytical approaches or by comparison with other methods.

• Work within the product team to deploy models to production software, with emphasis on software architecture, testability, security, and scalability.

• Document software theory for consumption by end users and the team. Disseminate own work to the wider team and to other stakeholders.

• Publish work in a variety of forms including journals or conferences, user meetings, webinars and blogs.

At Arup, you belong to an extraordinary collective – in which we encourage individuality to thrive. Our strength comes from how we respect, share and connect our diverse experiences, perspectives and ideas. 

You will have the opportunity do socially useful work that has meaning – to Arup, to your career, to our members and to the clients and communities we serve.

Is this role right for you? 

We’d like to hear from candidates who:

• Hold a Masters/PhD in an interdisciplinary area covering one or more of: machine learning, numerical analysis/scientific computing, computational mechanics, scientific machine learning. 
• Have research experience in the areas of learning operators and modelling surrogates, including but not limited to Physics Informed Machine Learning, Graph Neural Networks, and Reduced Order Modelling.
• Have proven technical ability in the area evidenced by excellent peer-reviewed publications in top academic journals.
• Demonstrate experience in Python with high level of comfort with common deep learning frameworks such as PyTorch or equivalent.
• Have experience using simulation software and solvers such as Ansys/LST LS-DYNA, Abaqus, Nastran and Altair and with creating numerical software in a commercial or open-source setting.
• Have knowledge of C++.
• Are familiar with software engineering tools (source control, JIRA, profilers, libraries) and software development processes such as Agile, test-driven development and coding standards.

Not ready to apply just yet, or have a few questions? Contact Marek Mazurowski ([email protected]). Please note, to ensure we remain GDPR compliant do not send your CV directly to us via this email.

What we offer you

At Arup, we care about each member’s success, so we can grow together.

Guided by our values, we provide an attractive total reward package that recognises the contribution of each of our members to our shared success. As well as competitive, fair and equitable pay, we offer a career in which all of our members can belong, grow and thrive – through benefits that support health and wellbeing, a wide range of learning opportunities and many possibilities to have an impact through the work they do. 

We are owned in trust on behalf of our members, giving us the freedom, with personal responsibility, to set our own direction and choose work that aligns with our purpose and adds to Arup’s legacy. Our members collaborate on ambitious projects to deliver remarkable outcomes for our clients and communities. Profit Share is a key part of our reward, enabling members to share in the results of our collective efforts.
We also provide Private medical insurance, Life assurance, Accident insurance and Income protection cover. In addition, you’ll have access to flexible benefits to help you look after all aspects of your wellbeing and give you the freedom and flexibility to find the best solutions for you, your family, and your individual needs.

Different People, Shared Values

Arup is an equal opportunity employer that actively promotes and nurtures a diverse and inclusive workforce. We welcome applications from individuals of all backgrounds, regardless of age (within legal limits), gender identity or expression, marital status, disability, neurotype or mental health, race or ethnicity, faith or belief, sexual orientation, socioeconomic background, and whether you’re pregnant or on family leave. We are an open environment that embraces diverse experiences, perspectives, and ideas – this drives our excellence. 

Guided by our values and alignment with the UN Sustainable Development Goals, we create and contribute to equitable spaces and systems, while cultivating a sense of belonging for all. Our internal employee networks support our inclusive culture: from race, ethnicity and cross-cultural working to gender equity and LGBTQ+ and disability inclusion – we aim to create a space for you to express yourself and make a positive difference. 

Discover more about life at Arup at www.arup.com/careers/your-life-at-arup.

We are committed to making our recruitment process and workplaces accessible to all candidates. Please contact Marek Mazurowski ([email protected]) to let us know if you need any assistance or reasonable adjustments throughout your application or interview process, and/or to perform the essential functions of the role. We will do everything we can to support you.

Our Application Process

To understand what to expect next, please visit our https://www.arup.com/careers/recruitment-process/. 

Stay safe online - Arup will never ask for payment or your bank details as part of our recruitment process.

Recruitment Agencies - We have a Preferred Supplier List of trusted partners to assist us when required and do not acknowledge any speculative CVs or unsolicited candidate introductions from agencies not on the list.

Closing date: 24th October 2025

We may close the role earlier than the advertised date should we receive a large number of applications, so please ensure you apply early.