Lecturer/Senior Lecturer Data Science for Earth and Environmental Sciences

The University of Manchester
Manchester
1 day ago
Create job alert

A Lecturer/Senior Lecturer in Data Science for Earth and Environmental Sciences is sought to support both research and teaching within the Department at the University of Manchester.

The Department of Earth and Environmental Science at University of Manchester has an international reputation for research across the geosciences in Environmental, Earth and Planetary Science. We consistently deliver internationally leading research, research impact and teaching, with a strong focus on applied geoscience research. AI and, more broadly, data science is revolutionizing geoscience by improving data analysis, interpretation, and predictive modelling. We therefore seek a new appointment to add capacity to our expertise in this area. We have particular interest in, but are not restricted to, expanding our data science capabilities across the earth sciences. The Department offers unrivalled facilities for geology, geophysics and data science, including world-class University of Manchester (UoM) facilities in Research Computing, workstation capacity for geophysical and remote sensing data interpretation and GIS; 2D multi-scale petrographical imaging and 3D-4D X-ray CT imaging facilities and a wide range of world leading experimental and analytical laboratories.

The University of Manchester occupies a uniquely storied position in the history of artificial intelligence; it was here that Alan Turing wrote his seminal paper laying the conceptual foundations for modern AI, and where the world's first stored-programme computer ran in 1948. Data science and AI are now embedded as a core strategic priority for the university, making this a particularly compelling moment to join. For an incoming academic in earth and environmental science, the opportunity is especially timely: AI@Manchester's research explicitly spans urban, energy, and environmental application areas, meaning your work sits squarely within an established and growing institutional focus. The university also maintains strong partnerships with the Alan Turing Institute and the European Laboratory for Learning and Intelligent Systems (ELLIS), offering rich opportunities for interdisciplinary collaboration at the intersection of data science and environmental challenges.

In addition to joining this vibrant research landscape, the new appointee will support teaching delivery on our successful undergraduate and masters programmes in Earth and Planetary Science, Environmental Science, Geoscience for Sustainable Energy, Petroleum Geoscience, and Pollution and Environmental Control, and in particular the cross-faculty MSc in Data Science. The post holder will also bring their personal research to students through supervision of individual or group projects across the spectrum from undergraduate to postgraduate research students.

The Department of Earth and Environmental Science is committed to promoting equality and diversity, including the Athena SWAN charter for promoting diversity in careers in the STEMM subjects (science, technology, engineering, mathematics and medicine) in higher education. The School of Natural Sciences to which the Department belongs holds an Athena SWAN Silver award, while the University holds a Race Equality Charter silver award. We welcome applications from all sections of the community especially those historically underrepresented in academia and appointment will be made on merit.

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

Related Jobs

View all jobs

2 Senior Lecturer / Lecturer (Asst Prof) and other positions in Machine Learning in Manchester, UK

Research Associate (Data Scientist) - City Futures Research Centre

Research Associate (Data Scientist) - City Futures Research Centre

Research Associate (Data Scientist) - City Futures Research Centre

Research Associate (Data Scientist) - City Futures Research Centre

Research Associate (Data Scientist) - City Futures Research Centre

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.