Research Associate in Computational Fluid Dynamics

The University of Manchester
Manchester
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Research Associate in Machine Learning for Spontaneous Inner Speech Detection - 0927-25

Lecturer/Senior Lecturer Data Science

Data Science Research Associate – Pregnancy Studies

Research Assistant/Associate in Exoplanetary Remote Sensing and Data Science (up to 2 posts) (F[...]

Exoplanetary Remote Sensing & Data Science Postdoc

Medical AI & Data Science: Associate Professor

We seek to appoint a research associate in Computational Fluid Dynamics, as part of an Innovate UK project working on the development of multi-fidelity modelling of fatigue and wear in hydrogen engines. The current appointment is for an initial 30 months, thought there is likely to be an opportunity for extension.

The successful candidate will work as part of an interdisciplinary team towards the aim of developing a digital tool for the design of key products in hydrogen fueled powertrains, enabling the prediction and mitigation of component failure when exposed to hydrogen operating environments. The multi-fidelity approach to be adopted seeks to combine predictions with different levels of accuracy into a reduced order model for the purpose of design exploration and evaluation.

The candidate should have knowledge and working experience of various approaches for the prediction of turbulence modelling & simulation, along with an interest to apply this expertise to complex industrial cases involving conjugate heat transfer and thermomechanical fatigue.

The successful candidate will have completed a PhD (or equivalent) in a related area and will have a strong teamwork mentality and a growth mindset. The selection committee will look for evidence of some or all of the following; significant programming experience, experience in the application of machine learning techniques to CFD, advanced data analysis skills and a track record of successful dissemination of their research via top journal papers and oral presentation at international conferences.

What you will get in return:

  • 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

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.

Our University is positive about flexible working you can find out morehere

Hybrid working arrangements may be considered.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any CV’s submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Prof Alistair Revell

Email:

General enquiries:

Email:

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.


Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.