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Gojan School of Business and Technology

Gojan School of Business and Technology | World University Rankings | THE

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United Kingdom, Liverpool

Liverpool John Moores University (LJMU) is a distinctive, unique institution, rooted in the Liverpool City Region and with a global presence. Our students and staff, past, present, and future, are the beating heart of our city and can be found in every corner of every industry and community. We couldn’t exist anywhere else and have shaped the city in which we belong. Working with the people of Liverpool to improve lives and support communities is at the heart of why we were founded and why we exist today.

We are seeking an experienced and highly organised Work-based and Placement Learning Senior Administrator to join our Faculty of Health, Innovation, Technology and Science (HITS). This is an exciting opportunity for a proactive professional to play a key role in the delivery, governance and continuous improvement of work-based and placement learning activities across a diverse portfolio of programmes.

As the Senior Administrative Lead within the Work-based and Placement Learning Team, you will provide specialist support for placement and work-based learning activities, ensuring compliance with university regulations, professional body requirements and external reporting obligations.

You will be responsible for overseeing complex administrative processes, supporting placement management systems, coordinating student placement activity and acting as a key point of contact for students, academic colleagues, employers, placement providers and external agencies.

Working closely with the Work-based and Placement Learning Manager, you will contribute to strategic and operational developments, support process improvement initiatives and help ensure an efficient, compliant and student-focused service.

In return, we offer an excellent benefits package including generous annual leave entitlement, pension scheme, induction and development support as well as family-friendly policies.

This is an exciting time to join the university as we deliver the LJMU Strategy 2030 and its vision of LJMU as an inclusive civic university transforming lives and futures, by placing students at the heart of everything we do.

If you feel that this is the role you have been looking for and your skills and experience can make a real difference at LJMU, we look forward to hearing from you.

Please note we do not accept supplementary information when considering applications for this post and ask that you complete the on-line application only. Within the application form there is the opportunity for you to include everything that you wish panel members to consider, particularly in the Personal Statement section.

LJMU values diversity and provides a supportive and inclusive environment where everyone can fulfil their potential.

Please note all of our vacancies will be closed to applications at midnight on the advertised closing date, unless otherwise stated.


Liverpool John Moores University (LJMU)

Singapore

Schemes of Service: Research
Division: Infocomm Technology
Employment Type: Fixed Term

Introduction

As a University of Applied Learning, the Singapore Institute of Technology (SIT) collaborates actively with industry in our research work. We seek a motivated candidate who is keen on rigorous research, the practical applications of code exfiltration and reverse engineering as well as security penetration testing.

The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of a research team to investigate and determine potentially critical Commercial Off-The-Shelf (COTS) drone system vulnerabilities impacting confidentiality, integrity and availability.

Key Responsibilities


	Participate in the research project with Principal Investigator (PI), Co-PIs and research team members to ensure all project deliverables are met.
	Undertake or help guide work and demonstrations in the following tasks:
	
		Code exfiltration and binary reverse engineering.
		Study, understand and analyse mobile platform applications.
		Android app reverse engineering (Drone apps)
		Static and Dynamic analysis(experience in tools like Frida, Burp, Wireshark)
		Develop AI-assisted agents for automated firmware analysis and exploration
		Build a controlled firmware-replica environment for evaluating protocol security
		Design, develop and test control augmentation techniques.
		Adaptation of developed techniques for more generic use.
	
	
	Perform project documentation and crafting of research papers.
	Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
	Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.


 Job Requirements


	A good degree in Computer Science / Engineering or higher.
	Proficiency with code exfiltration and reverse engineering.
	Proficiency with penetration testing techniques and tools.
	Proficiency with software scripting and development work on desktop and / or mobile platforms.


Key Competencies


	Self-directed learner who believes in continuous learning and development.
	Possess strong analytical and critical thinking skills.
	Show strong initiative and take ownership of work.
	Proficient in technical writing and presentation.
	Able to build and maintain good working relationships with people within and external to the university.



Singapore Institute of Technology (SIT)

United Kingdom, Durham

The School of Education is one of the very best UK Education departments with an outstanding reputation for excellence in teaching and research. We were ranked 2nd for Outstanding Research in Education and 1st for Impact and Outputs in the most recent Research Excellence Framework (REF 2021), ranked 2nd in the Complete University Guide 2026 and have a top 100 ranking in the QS World University Rankings by subject 2026.

Guiding the School of Education's research activity is our vision of a more equitable world in which education, informed by innovative high-quality research, plays a vital role in enabling individuals, communities and societies to flourish. To this end, our research and impact strategy enables us to undertake research that: 1) positively impacts on regional, national and global policy and practice; and 2) shapes and develops educational research, research methodology and research capacity in the UK and internationally.

This role would be research only, working on an externally funded research project with a team of evaluation, early years and literacy development experts. The School of Education supports hybrid working and flexible working if required.


Durham University

Schemes of Service: Research
Division: Infocomm Technology
Employment Type: Fixed Term

Project Overview

We are seeking an outstanding and highly motivated Research Fellow (PhD) or Research Engineer (Master's degree) to join an exciting research project on Artificial Intelligence for intelligent railway inspection and predictive maintenance.

The project aims to develop next-generation AI solutions for the automatic inspection of train components with multi-modal sensor data, enabling early detection of defects and supporting safer, more reliable, and more efficient railway operations. The successful candidate will conduct cutting-edge research and develop robust AI models capable of analysing inspection data, identifying defects, and assisting maintenance decision-making.

The project is conducted in close collaboration with industry partners and offers the opportunity to work on real-world challenges with significant practical impact.

Key Responsibilities

The successful candidate will be responsible for:


	Conducting research and development on AI-based solutions for automated defect inspection and condition assessment of train components by designing and developing deep learning, computer vision, and machine learning algorithms.
	Collaborating with industry partners to understand operational requirements and developing AI pipelines for analysing visual and sensor data collected during inspection processes.
	Building, training, validating, and deploying AI models for industrial deployment.
	Designing experiments and evaluating the performance and robustness of developed algorithms.
	Preparing technical reports, research publications, presentations, and project deliverables.
	Assisting in supervising junior researchers and students where appropriate.


Job Requirements


	PhD (for Research Fellow) / Master's degree (for Research Engineer) with expertise in Computer Science, Artificial Intelligence, Computer Vision, Machine Learning, Robotics, or a closely related field.
	Experience in developing, training, validating and deploying AI models for industrial inspection, predictive maintenance, or asset condition monitoring.
	Strong analytical, problem-solving, and software development skills.
	Ability to conduct independent research while working effectively within a multidisciplinary team.
	Written and verbal communication skills.


Key Competencies


	Proven experience in developing AI solutions for industrial inspection, predictive maintenance, or asset condition monitoring.
	Hands-on experience in deploying AI systems in industrial environments.
	Experience with defect detection, anomaly detection, or visual inspection systems.
	Familiarity with multimodal sensing technologies, including RGB imaging, thermal imaging, 3D vision, or other non-destructive inspection methods.
	Experience with edge AI, real-time inference, or MLOps for industrial applications.
	Knowledge of railway systems, transportation engineering, or infrastructure inspection.
	Experience in collaborating with industry partners and delivering applied research.



Schemes of Service: Research
Division: Infocomm Technology​​​​​​​
Employment Type: Fixed Term

Introduction

As a University of Applied Learning, the Singapore Institute of Technology (SIT) collaborates actively with industry in our research work. We seek a motivated candidate who is keen on rigorous research, the practical applications of code exfiltration and reverse engineering as well as security penetration testing.

The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of a research team to investigate and determine potentially critical Commercial Off-The-Shelf (COTS) drone system vulnerabilities impacting confidentiality, integrity and availability.

Key Responsibilities


	Participate in the research project with Principal Investigator (PI), Co-PIs and research team members to ensure all project deliverables are met.
	Initiate and help guide work and demonstrations in the following tasks:
	
		Firmware extraction and reverse engineering.
		Study, understand and analyse mobile platform applications.
		Design, develop and test AI-driven security testing techniques.
		Design, develop and test control augmentation techniques.
		Adaptation of developed techniques for more generic use.
	
	
	Perform project documentation and technical mentoring of student assistants.
	Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
	Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.


 Job Requirements


	A good degree in Computer Science / Engineering, preferably with a relevant postgraduate qualification for Research Fellow.
	Proficiency with firmware extraction and reverse engineering.
	Proficiency with penetration testing techniques and tools.
	Proficiency with software scripting and development work on desktop and / or mobile platforms.


Key Competencies


	Self-directed learner who believes in continuous learning and development.
	Possess strong analytical and critical thinking skills.
	Show strong initiative and take ownership of work.
	Proficient in technical writing and presentation.
	Able to build and maintain good working relationships with people within and external to the university.



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