Computer Science Teacher

Uxbridge South
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Lecturer in Computer Science (Data Science)

Assistant Professor in Data Science

Computer Vision internship - West London

Computer Vision Engineer - (Remote - UK, Ireland and Hungary)

Principal Data Science Consultant with Marketing Expertise

Principal Data Science Consultant - Financial Services Expertise

Department: Computer Science – Key Stage 3, Key Stage 4, Key Stage 5

Inspire the Next Generation of Tech Innovators

A fantastic secondary school in Uxbridge is seeking a passionate and dedicated Computer Science Teacher to join its growing department. The school is committed to providing a cutting-edge digital learning environment where students develop essential programming, problem-solving, and computational thinking skills to prepare them for the modern technological world.

The Role

The successful candidate will:

  • Deliver engaging and high-quality Computer Science lessons across Key Stage 3, Key Stage 4, and Key Stage 5.

  • Teach core topics such as Python programming, algorithms, data structures, cybersecurity, and artificial intelligence.

  • Inspire students to develop computational thinking and technical problem-solving abilities.

  • Contribute to the ongoing development of an innovative and challenging Computer Science curriculum.

  • Use state-of-the-art technology, coding platforms, and digital resources to enhance learning experiences.

  • Assess, monitor, and support student progress, providing tailored feedback to maximise achievement.

  • Engage in extracurricular activities such as coding clubs, hackathons, and partnerships with the tech industry.

    Candidate Requirements

    The ideal candidate will:

  • Be a qualified teacher (QTS/QTLS) with a strong background in Computer Science.

  • Have experience teaching Computer Science to A-Level, with a proven track record of student success.

  • Be passionate about technology, coding, and innovation in education.

  • Demonstrate excellent subject knowledge and classroom management skills.

  • Work collaboratively within the Computer Science department to maintain high teaching standards.

    Investment in Digital Learning

    The school has made significant investments in its Computer Science Department, providing access to high-spec computer labs, industry-standard software, and cutting-edge AI and robotics tools. As a result, students consistently achieve excellent A-Level results, with many progressing to top universities and careers in software development, cybersecurity, and data science. The department is committed to delivering hands-on, project-based learning to equip students with real-world skills.

    Why Join This School?

  • Outstanding Facilities – Teach in modern computer labs equipped with the latest technology.

  • Strong Tech Faculty – Be part of a dedicated and high-achieving department.

  • Career Development – Access CPD and leadership opportunities to enhance professional growth.

  • Student Success – Join a school where A-Level Computer Science students achieve impressive results year after year.

  • Prime Location – Situated in Uxbridge, with great transport links and a vibrant local community.

    Application Process

    If you are a passionate and ambitious Computer Science Teacher, applications are welcome.

    How to Apply:

    Interested candidates should submit their CV detailing their suitability for the role to Lorenzo Fuller or call me on (phone number removed).

    The school is committed to safeguarding and promoting the welfare of children and young people. All appointments are subject to an enhanced DBS check and satisfactory references

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 Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

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

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.