Technical Manager - Healthcare Science - NHS GGC Microbiology

NHS Greater Glasgow & Clyde
Glasgow
3 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Licensing & Tools Applications Engineer

Product Manager

Pricing Data Science Manager

Pricing Data Science Manager

Pricing Data Science Manager

Information and Data Governance Lead

NHS Greater Glasgow and Clyde is one of the largest healthcare systems in the UK employing around 40,000 staff in a wide range of clinical and non-clinical professions and job roles. We deliver acute hospital, primary, community and mental health care services to a population of over 1.15 million and a wider population of 2.2 million when our regional and national services are included.

The Microbiology Technical Manager post at QEUH Microbiology is responsible for a sub-division of the department under the direction of the Operational Manager. The post holder will perform as lead specialist in designated areas of responsibility. The post holder will provide direction to staff and provide highly specialist advice to service users (clinicians, GPs, nurses etc.), colleagues and other senior staff such as department consultants and laboratory managers.

The Diagnostic Clinical Microbiology/Virology Service for NHS Greater Glasgow & Clyde (NHS GG&C) is delivered from two sites: Glasgow Royal Infirmary and the Queen Elizabeth University Hospital. The laboratories provide a full and comprehensive Microbiology / Virology service to the population of NHS GG&C including Hospital based users, General Practice users, Private Sector users and to colleagues in the university and teaching sectors.

Applicants must be registered with the Health Care Professions Council (HCPC) as a Biomedical Scientist and hold an MSc Biomedical Science educational qualification or hold the Fellowship of the Institute of Biomedical Science (F.I.B.M.S.) or have an equivalent educational qualification.

The post is based at the Microbiology Laboratory, Queen Elizabeth University Hospital, Glasgow which is a state of the art facility which contains extensive microbiology equipment such as Vitek 2, Vitek MS, Virtuo, WASPLab and MGiT TB Analysers. The laboratory processes around 420,000 specimens per annum and in addition to routine microbiology sections, also provides a paediatric microbiology service to the Royal Hospital for Children and Cystic Fibrosis Microbiology service for CF adults and children.

The laboratory holds UKAS accreditation for ISO 15189 standards as a single managed unit together with the Microbiology laboratory at Glasgow Royal Infirmary.

A laboratory out of hours / shift service operates whereby the post holder will be required to work 37.0 hours over 7 days including evenings, weekends and public holidays as a contractual requirement. This involves the post holder carrying out, without supervision or the immediate on site availability of medical or technical advice, any of the tasks for which they are trained. It is the nature of this 24/7 service that the work is of an urgent or emergency nature and often involves the more complex diagnostic tasks e.g. those used in the diagnosis of meningitis or septicaemia

Details on how to contact the Recruitment Service can be found within the Candidate Information Packs.

NHS Greater Glasgow and Clyde encourages applications from all sections of the community. We promote a culture of inclusion across the organisation and are proud of the diverse workforce we have.

By signing the Armed Forces Covenant, NHSGGC has pledged its commitment to being a Forces Friendly Employer. We support applications from across the Armed Forces Community, recognising military skills, experience and qualifications during the recruitment and selection process.

Candidates should provide original and authentic responses to all questions within the application form. The use of artificial intelligence (AI), automated tools, or other third-party assistance to generate, draft, or significantly modify responses is strongly discouraged. By submitting your application, you confirm that all answers are your own work, reflect your personal knowledge, skills and experience, and have not been solely produced or altered by AI or similar technologies.

Failure to comply with this requirement may result in your application being withdrawn from the application process.

For application portal/log-in issues, please contact in the first instance

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.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.