Cyber Security Researcher - AI / ML

Conexus DX Limited
Newport
11 months ago
Applications closed

Related Jobs

View all jobs

Hybrid Machine Learning Engineer - Build Impactful Models

Machine Learning Engineer Contractor

Research Fellow in Machine Learning for Hydroclimatology

MSc Data Science and Artificial Intelligence

Online MSc in Data Science & AI - Flexible, Part-Time

Lead Data Scientist

Join a cutting-edge team focused on digital security research and innovation, driving the development of solutions to complex problems in the digital security domain. As a Cyber Security Innovation Specialist, you will lead projects, provide consultancy, and collaborate across internal and external networks to ensure the business remains at the forefront of technological advancements.

12-month rolling contract up to 3 years | Strong Hourly Rate | Overtime Available | Hybrid Working | Flexible Working Hours | Fast Interview / Hiring Process

Key Responsibilities

  • Coordination: Facilitate cyber security innovation activities across the organisation, build working networks, and represent the Digital Security Office at conferences and events.
  • Collaboration: Work with peers and partners to integrate cyber security into projects and maintain external innovation agreements.
  • Consultancy: Offer expert advice and training in your specialist area of cyber security innovation.
  • Innovation: Conduct research, develop prototype solutions, and maintain a cyber innovation roadmap addressing future threats and opportunities.

Requirements

Academic

  • Must Have: Bachelor's degree in Artificial Intelligence/Machine Learning and recent PhD or Master's in Cyber Security of AI/ML.
  • Advantage: Professional training or certifications in cyber security.

Experience

  • Must Have: Expertise in AI/ML algorithms and applications, with experience in research or solution development.
  • Advantage: Publications in cybersecurity, patent experience, and knowledge of AI/ML vulnerabilities.

Technical Expertise

  • Must Have: Specialist knowledge in AI/ML techniques.
  • Advantage: Experience in cybersecurity-focused AI/ML tools, vulnerabilities, and programming languages such as Python or Rust.

Outputs

  • Prototype solutions, technical reports, and market studies.
  • Contributions to academic funding, patents, and publications.

This role offers an exciting opportunity for a motivated individual to lead innovation in digital security and shape the future of cyber technology. Apply now to be at the forefront of this dynamic field!

SmFtaWUuSGluZS44MjU0Ny4xMjI3MUB5b2xrLmFwbGl0cmFrLmNvbQ.gif

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.