PhD Studentship in Data-driven mechanics

University of Cambridge
Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Researcher Statistics Python AI

Data Scientist Intern (PhD level)

Data Scientist Intern (PhD level)

Actuarial Data Science: Assistant Professor, Edinburgh

Exoplanetary Remote Sensing & Data Science Postdoc

Medical AI & Data Science: Associate Professor

Mechanical properties of materials are usually measured by simple one-dimensional tests. The growing field of data-driven mechanics requires development of experimental methods to obtain large quantities of multi-axial data from a single test. To complement this data is the requirement to develop computational methods that can deal with the inevitable measurement noise. We are starting a new project with the aim to use: (i) lab-based flux enhanced tomography for full field measurement of deformation fields and X-ray diffraction measurements of elastic strains, and (ii) associated data-driven material model discovery techniques. These coupled measurements and machine learning techniques are expected to form an important element in the field of data-driven mechanics. We are looking for a PhD student to join the project to work alongside post-doctoral associates and our partner universities in the US.

Applicants should have (or expect to obtain by the start date) at least a high 2.1 degree (preferably a first or its equivalent) in Engineering, Physics or related subject. A strong interest in multi-physics modelling and/or experimental methods is essential. This studentship is open to both home and overseas applicants.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

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.

Jobs

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Education Jobs

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Jobs

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.