Lecturer in Computing x 3

Glasgow Caledonian University
Glasgow
2 years ago
Applications closed

Related Jobs

View all jobs

Lecturer in Computing (HE) (Data Science and AI)

Lecturer in Computing (HE) (Data Science and AI)

Lecturer in Music & Data Science — Lead MSc Program

Lecturer (Teaching and Scholarship) in Music and Data Science

Music & Data Science Lecturer — Teaching & Research

Remote Data Science Module Lead (Online Lecturer)

Advert

The roles are full time but we will consider requests for flexible workingarrangements, including job share

Glasgow Caledonian – the largest and leading modern university in Scotland - is a vibrant, values-led university with campuses in the heart of Glasgow and London. With a strong commitment to high quality education and research which supports the communities we serve, we have strong partnerships with employers to ensure our students get the careers they dream of and deserve.

In we rocketed into the top universities in the UK in the highly regarded Guardian University Guide, were ranked the UK’s nd top performing modern university in the inaugural Daily Mail guide, and entered the top highly coveted UK universities in the Times and Sunday Times Good University Guide for the first time. We are the top performing modern University in Scotland in all three guides. We are the only Scottish university with EcoCampus Platinum accreditation and were ranked second in Scotland for sustainability in the most recent People and Planet league table.

With a wide range of professionally accredited courses and links with over industry partners, we have the highest proportion of undergraduate level graduates in highly skilled occupations (%) compared to other Scottish modern universities - with % of our students in employment or further study within fifteen months of graduating (HESA ). We are Scotland’s leading provider of Graduate Apprenticeships. We are committed to widening participation, helping more people from diverse backgrounds into university. With campuses in Glasgow, London and New York, we have transnational partnerships around the world, supporting more than , students from nearly countries.

Our research is addressing many of today’s biggest global challenges. We are unsurpassed by any other Scottish modern university for the level of research (%) considered to be world leading or internationally excellent. Our health research is surpassed only by King’s College London for outstanding impact, and % of our communications, culture and media research is rated as having an outstanding or very considerable impact (REF).

Guided by our values – integrity, responsibility, creativity and confidence - we transform the lives of the people and communities we serve.

The Department of Computing, within the School of Computing, Engineering and Built Environment is a dynamic and vibrant academic community with a strong track record of applied research, innovative teaching and award-winning knowledge transfer activities. We wish to appoint an enthusiastic academic who can play a leadership role in the School, has relevant research expertise, and can deliver on technical modules in the Computing and Software Engineering areas at undergraduate and postgraduate level.

The successful candidates will hold a PhD, or a relevant Masters qualification level and be enrolled on a PhD programme which they are likely to complete within months, and/or equivalent significant industry experience along with membership of a relevant professional body. We are seeking individuals who have a passion and enthusiasm to deliver innovations in learning and teaching and to enhance our research and our knowledge exchange activities. Areas of expertise required include but are not limited to Software Development, Software Engineering, Data Science, Artificial Intelligence, Cloud Computing, Data Engineering, Internet of Things and Secure Software Development.

All applicants must complete the online application form detailing how they meet the essential and desirable requirements for the role. A short covering letter highlighting why you feel you are suitable for this position (-page maximum) and a short, summary CV ( pages maximum) may also be included.

As the University for the Common Good, we are committed to embedding equality, diversity and inclusion, as well as our values in everything that we do. As such, we welcome applications from all suitably qualified candidates who demonstrate the .

Glasgow Caledonian University is committed to a fair and transparent recruitment process that is free from bias so that we can attract and retain a high performing workforce which makes a critical contribution to our success​.

The University holds the prestigious Athena SWAN Silver institution award, which recognises our significant record of activity and achievement in promoting gender equality across different disciplines.

The School of Computing, Engineering and Built Environment is committed to promoting equality, diversity and inclusion, and is one of only two such Schools in Scotland to hold the prestigious Athena SWAN Silver Award for promoting gender equality and women’s careers in STEMM subjects (science, technology, engineering, mathematics and medicine) and allied STEMM subjects (surveying, environment and management of all themes) in higher education.

As a Disability Confident 'Committed' employer, we are striving to ensure that our recruitment process is inclusive and accessible to disabled people. Although the Disability Confident 'Committed' level does not guarantee an interview for disabled applicants, we will make reasonable adjustments for disabled applicants during the recruitment process.

The University also holds the Carer Positive ‘Engaged’ employer award, which recognises our commitment to supporting staff with caring responsibilities.

Glasgow Caledonian University are committed signatories to the . 

The University offers a range of benefits including opportunities for professional development, family friendly policies, cycle to work scheme and onsite childcare facilities.

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 to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

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

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

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.