National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Postdoctoral Research Associate in Aerospace Engineering: UAV or Sports Aerodynamics

Heriot-Watt University
Midlothian
1 year ago
Applications closed

Related Jobs

View all jobs

Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials

Senior Data Scientist

Postdoctoral Researcher in UAV or Sports Aerodynamics 

Directorate: School of Engineering & Physical Sciences 

Salary: Grade 7 (£36,023-£45,585)

Contract Type: Full Time (1FTE), Fixed Term (3 Years) 

Detailed Description 

We are seeking to appoint one outstanding Postdoctoral Researcher with a passion for computational modelling and experimental validation in aerodynamics with aspirations of an academic career. The position will be aligned with advancing research in the new research group of Aerospace Engineering at Heriot-Watt University. The selected candidate will work under the supervision of Professor Bert Blocken. 

Applicants should hold a PhD in Aerospace Engineering, Mechanical Engineering (specialisation Fluid Mechanics), Civil Engineering (specialisation Fluid Mechanics) or the like. Proven excellent expertise in CFD modelling is a strict requirement, additional expertise in wind tunnel testing is a plus. Expertise in integrating Artificial Intelligence in aerodynamics is also a plus. 

The selected candidate should ideally have familiarity with and will work on one or several of the following topics: 

Autonomous flight systems, with focus on pushing the boundaries for unmanned aerial vehicles  Sports aerodynamics, with focus on pushing the boundaries in cycling and athletics 

In these topics, a large focus will be placed on CFD modelling, wind tunnel tests in the new-to-be-built large wind tunnel of Heriot-Watt University (inauguration expected in 2025) and on-site testing. Integration of Artificial Intelligence in these topics will be expected. 

Applicants are expected to have excellent verbal and written communication skills, with a demonstrated ability to write refereed journal articles and present work at scientific/engineering conferences. 

This full-time position is based in the Institute of Mechanical, Process and Energy Engineering of the School of Engineering and Physical Sciences at Heriot Watt University. It is funded for up to 3 years in the first instance. If the Postdoctoral Researcher can demonstrate strong research output and the ability to generate sufficient financial income, the position might transition into a permanent appointment as full member of the university’s academic staff (nominally Assistant Professor in the first instance). This will be dependent on achieving clear goals that will be set at the start of the appointment period in consultation with the corresponding Head of Research Institute and approved by Executive Dean. 

While the post is primarily research-focused, teaching experience is an important part of a post-holder’s professional development in order to transition into a member of the Academic Staff. Accordingly, an appropriate contribution in support of teaching in the School of Engineering and Physical Sciences will be expected. 

Key Duties and Responsibilities 

Manage projects in terms of the simulation methodology that is most applicable, running simulations and curating the data.  Provide input for wind tunnel design and testing and using output for high-quality CFD validation.  Be an innovator, by developing and expanding the research project over time, and presenting novel ideas.  Collaborate in and/or lead in the preparation of scientific peer-reviewed articles and present papers, posters and talks.  Act as a source of information and advice to other members of the group on CFD simulation techniques and wind tunnel testing.  Represent the research group, Aerospace Engineering and Heriot-Watt University at meetings and conferences, either with other members of the group or alone.  Mentor junior members of the group (PhD students or undergraduate project research students).  Optional: Develop research proposals including for an Independent Fellowship 

Please note that this job description is not exhaustive, and the role holder may be required to undertake other relevant duties commensurate with the grading of the post. Activities may be subject to amendment over time as the role develops and/or priorities and requirements evolve. 

Education, Qualification and Experience 

Essential Criteria 

The candidate will: 

Hold a PhD in Aerospace Engineering, Mechanical Engineering (specialisation Fluid Mechanics), Civil Engineering (specialisation Fluid Mechanics) or a related field.  Be able to demonstrate competence and success as achieved in the PhD research (and postdoctoral work if appropriate), e.g. as judged by publications in high quality peer-reviewed journals. Evidence will be sought of a deep understanding of the applicant's previous fields of research and evidence of independent intellectual and practical contributions to previous research projects.  Be able to articulate a clear vision for development of their independent research activity.  Demonstrate experience and regular use of/contribution to Ansys CFD, OpenFOAM or a similar CFD code.  Possess excellent communication skills, including the ability to lead the writing of journal articles, present research proposals and results, and represent the research group at meetings.  Show an ability to work supportively with other academicians and with technical staff in a laboratory environment, and to supervise and mentor junior co-workers.  Have proven HPC skills. 

Desirable Criteria 

Familiarity with active and unique contributions to OpenFOAM, Ansys CFD, or the like  Familiarity with advanced computer programming  Experience in machine learning methods 

About our Team

The School of Engineering & Physical Sciences (EPS) was created in August 2002. We are a community of over 340 staff and around 3,000 students across our three campuses in Scotland, Dubai and Malaysia. The School is recognised as an international leader in education, research and the application of knowledge to benefit society globally, committed to excellence with a purpose. We are striving to establish ourselves as partners of choice for world leading institutions, consistently delivering an environmentally and financially sustainable growth by aligning to the opportunities and requirements of our modern times to address local and global needs 

Our research ranges from fundamental sciences through to engineering applications, all of which are supported by strong external funding. We have over 150 full-time academic staff who drive this research activity and are based in 5 research institutes: the Institute of Chemical Sciences, the Institute of Photonics & Quantum Sciences, the Institute of Mechanical, Process & Energy Engineering, the Institute of Sensors, Signals & Systems and the Institute of Biological Chemistry, BioPhysics & BioEngineering. In REF2021, our Physics was top in the UK for world-leading research outputs. Our joint submission to Engineering with the University of Edinburgh was ranked 1st in Scotland and 3rd in the UK for quality and breadth of research (based upon the standard Research Power formula as used by the Times Higher Education). 

We provide world-class education to our students across six undergraduate programmes: Chemistry; Physics; Electrical, Electronic & Computer Engineering; Chemical & Process Engineering; Mechanical Engineering and Brewing & Distilling and will soon add Aerospace Engineering to our undergraduate programme portfolio. We also offer a range of postgraduate taught programmes. In the recent The Times and Sunday Times Good University Guide 2023, our Chemical Engineering is the 6th in the UK (the 2nd in Scotland), Aeronautical & Manufacturing Engineering is the 7th in the UK (the 1st in Scotland) and General Engineering is the 9th in the UK (the 1st in Scotland). In the 2022 National Student Survey (NSS), we are ranked the 4th in the UK for overall satisfaction in Chemical Engineering, the 2nd in Scotland in Electrical Engineering and Physics, and are the top ranked in the UK in Food & Beverage discipline (which includes our Brewing & Distilling discipline, where we have achieved a 100% students overall satisfaction).

We are seeking an experienced and leading academic researcher to lead and develop research and teaching activities in areas related to advanced materials, aerospace or solid mechanics. 

The post holder will be line managed by the Head of the Institute for Mechanical, Process and Energy Engineering (IMPEE) and assigned teaching responsibilities by the Mechanical Engineering Senior Programme Director. 

National AI Awards 2025

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.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.