Applied Scientist Placement

Camlin Group
Lisburn
10 months ago
Applications closed

Related Jobs

View all jobs

AI Data Scientist: Applied Intelligence & Delivery

Senior Data Scientist (Applied AI)

Senior AI/ML Scientist, Applied NLP & Generative AI

Senior Machine Learning Scientist

Machine Learning Engineer (Applied AI) (100% Remote in EMEA)

Applied AI Data Scientist — Real-World Delivery (Cambridge)

Company Description:

Camlin is a global technology leader that operates with the vision of bringing revolutionary products to life for a wide range of industries, including power and rail, and also has interests in a number of R&D projects in a variety of scientific sectors.


At Camlin we believe in high quality engineering and design, allowing us to develop market leading products and services. In short, we love creating value for our customers by solving difficult problems. As of today, the Camlin operation spans over 20 countries across the globe.




What to expect day to day:

As a Student Placement within the Applied Sciences team at Camlin, you will have a unique opportunity to gain hands-on experience across multiple areas of research, development, and technical support. You will work closely with experienced Scientists and Engineers, contributing to real-world projects that enhance the capabilities of Camlin's product range. These include Dissolved Gas Analysis (DGA) for high-voltage asset monitoring, and gas sensors for Biogas/Biomethane applications.


This role is designed to broaden your technical skill set, offering exposure to laboratory work, data analysis, experimental design, and process improvement initiatives. You will be involved in various aspects of product development, from concept testing and prototyping to automation and data-driven decision-making. Your work will directly contribute to the continuous improvement of our technologies, supporting both research and operational teams.


Example Projects & Responsibilities:

During your placement, depending on your skills and previous experience, you may take on projects such as:


· Supporting research efforts for new technologies in our next generation of products.

· Designing and building a system to accelerate experimentation and product development.

· Extracting key performance statistics, automating data visualization, and displaying insights from our gas sensor production facility on a digital dashboard.

· Building a database, automating workflows, and improving data utilization from our DGA lab.


Beyond these projects, you will have the opportunity to engage in hands-on lab testing, data-driven investigations, and cross-functional collaboration, ensuring a well-rounded experience.


What we are looking for:

We're seeking a curious, proactive, and motivated student with a passion for Applied Science and Technology. You should be eager to learn, comfortable working with data, and enthusiastic about contributing to innovative solutions.


This placement will give you a strong foundation in Applied Research and Development, setting you up for a future career in Science, Engineering, or Technology.



Essential Criteria:

· Currently studying towards a Bachelor's or Master's degree in Engineering, Physics, Chemistry or a related discipline Interest in applied science and technology.

· Strong problem-solving abilities and a logical approach to troubleshooting technical challenges.

· Analytical mindset with an eagerness to learn data analysis and root cause analysis (RCA) methodologies.

· Enthusiasm for hands-on experimentation, with a willingness to perform tests and investigations under guidance.

· Ability to work collaboratively.

· A continuous improvement mindset, with a keen interest in streamlining workflows and automating processes.

· Attention to detail and an organised approach to lab work and data management.

· Effective communication skills to discuss findings and ideas with internal teams.

· Proactive approach to learning new skills and identifying trends in technical data.

· Flexibility and adaptability to take on a variety of tasks across different projects.



Nice to have but not essential:

· Previous lab experience, university projects, or internships related to Engineering, Physics, or Chemistry.

· Basic knowledge of gas sensing, spectroscopy, or sensor technologies.

· Familiarity with Python (or similar programming languages) for data automation and analysis.

· Experience working on technical projects that involve experimentation, prototyping, or testing.


Equal Employment Opportunity Statement

Individuals seeking employment at Camlin are considered without regards to race, colour, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, gender identity, or sexual orientation.



Aed6XlCN4oxjmf56OUPek1

PI265930488

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.

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

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

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.