Postdoctoral Research Assistant in Biometrics

TN United Kingdom
Reading
1 month ago
Applications closed

Related Jobs

View all jobs

Postdoctoral Research Assistant in Machine Learning

Postdoctoral Research Assistant in Computer Vision x2

Research Fellow in Genomic Data Science

Research Fellow in Genomic Data Science

Machine Learning Researcher | Deep Learning | Graph Neural Networks | Python | PyTorch

Research Scientist, Quantum Chemistry and Machine Learning, London

Social network you want to login/join with:

Postdoctoral Research Assistant in Biometrics, Reading

Client: University of Reading

Location: Reading, United Kingdom

Job Category: Other

EU work permit required: Yes

Job Reference:

a037a5021b2b

Job Views:

2

Posted:

19.03.2025

Expiry Date:

03.05.2025

Job Description:

Exciting opportunity to work in R&D in a ground-breaking EU border security project.

The Department of Computer Science within the School of Mathematical, Physical and Computational Sciences (SMPCS) conducts world-leading research in priority research areas of Data Science and Computational Science. Within the department, the Computational Vision Group (CVG), led by Prof. Ferryman, addresses the computational issues of perception and reasoning in relation to image interpretation.

Prof. Ferryman is Principal Investigator in the EC project CarMenhttp://www.carmen-horizon.eu/funded under the EC Civil security for society work programme (border security and external security). A key aim of CarMen is to build and deploy advanced identity verification tools for border security involving pedestrians and vehicles on-the-move. This is a fixed-term position ending on 31/08/2027.

The main role of the PDRA is to undertake biometric research and development.

Main duties and responsibilities:

  • Research, develop, implement and evaluate person identity verification technologies for border security, including one or more of: iris recognition and presentation attack detection, multimodal biometric fusion, biometric quality assessment and benchmarking in a biometrics on-the-move setting.
  • Programming in relevant language (e.g. Python) and use of/integration with relevant libraries including APIs to external SDKs/modules.
  • Contribute to the writing of papers for publication in leading academic journals and other relevant media.
  • Active role in project-related activities such as data collection, integration and demonstration/trials and evaluation.
  • Achievement of project objectives within tight time constraints, delivering software, writing reports, and academic publications, and giving presentations of work undertaken within the project.

You will have:

  1. PhD (or soon to obtain PhD) in relevant subject or discipline.
  2. Strong scientific background; knowledgeable of identity verification/management, including application of biometrics.
  3. Appropriate publication track record for career stage.
  4. Relevant programming skills.

Closing date: 20th April 2025
Interviews will be held: Week commencing 5th May 2025

Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. By reference to the applicable SOC code for this role, sponsorship may be possible under the Skilled Worker Route. Applicants should ensure that they are able to meet the points requirement under the PBS. There is further information about this on the UK Visas and Immigration Website.

The University is committed to having a diverse and inclusive workforce, supports the gender equality Athena SWAN Charter and the Race Equality Charter, and champions LGBT+ equality. Applications for job-share, part-time and flexible working arrangements are welcomed and will be considered in line with business needs.

#J-18808-Ljbffr

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.

Jobs

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.

Jobs Careers

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.