Research Assistant / Associate in Data and Physics-informed simulation of very large aircraft structures

Imperial College London
London
4 months ago
Applications closed

Related Jobs

View all jobs

Research Associate on EWADA Project

Admin Assistant

Lecturer in AI and Data Science

Junior Technical Writer

Director, AIML & Scientific Computing Optimization (Basé à London)

Director, AIML & Scientific Computing Optimization (Basé à London)

The position of Research Assistant/Associate in Data and Physics-informed simulation of very large aircraft structures is part of a large project funded by EPSRC, with close interaction and planned visits to AIRBUS and NASA. The goal of deploying a new generation of zero-emission aircraft within the next decades leads to a need to fundamentally re-think the role of simulation in aircraft design. In this role, you will be part of a team seeking to develop fundamentally new numerical methods, based on data and physics, for the simulation of very large structures. These methods, which will build upon extensive experience within the group, are intended to underpin the future design of new generations of aircraft.


You will be part of a team with Prof. Pinho, another PDRA and two PhD students, all working on this project. Visits to NASA, Airbus and other project partners are planned within the project, as well as deployment of the software at Airbus and validation against real full-wing test data part of Airbus’s Wing of Tomorrow project. You will also have opportunities to participate in the supervision of master’s projects.

You will use the Finite Element Method, Artificial Intelligence and Uncertainty Quantification, and will program using Python and C++ (. user elements, user materials, surrogate models, among others). The software you will contribute to will be made publicly available under a BSD-3 licence, and will be compatible with various FE solvers, so it achieves maximum impact and you gain maximum recognition. You will publish your results in the leading journals in the area, and will have the opportunity to attend various conferences to disseminate your work.

You will develop, implement and verify numerical methods which underpin the structural simulation, design and certification of very large structures, such as aircraft wings. You will use AI as appropriate in the development of such models, for instance for surrogate models of structural components. You will incorporate means for effective uncertainty quantification in said models. You will use professional software development standards to ensure that the codes are sustainable, readable, modular, reusable and optimised for HPC.


We are looking for applicants with sound knowledge of solid mechanics and experience on:

 Structural simulation using the Finite Element Method (Essential) Programming (. Python, Fortran, C++) (Essential) Artificial intelligence (. machine learning) (Desirable) Uncertainty Quantification (Desirable)


This role will offer you the following:

Be part of a world-leading research group with a proven track record of coming top in international academic benchmark exercises for their models, and of having their models used by industry and shipping natively within the leading finite element software packages The unique possibility to verify your predictions against a full-scale structural test of an aircraft wing via the interaction with Airbus’s wing of tomorrow programme The possibility to deploy of your codes at Airbus, and the possibility of a ‘technology transfer’ stay at Airbus The opportunity to visit NASA Langley Research Centre, and to further collaborate with NASA on model development The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity. Grow your career: Gain access to Imperial’s sector-leading as well as opportunities for promotion and progression Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.