Justin Leung

Institution: University of Manchester

Biography: I am a Computer Science graduate. For my final year university project, I developed a brain tumour segmentation model using Weakly Supervised Learning combining medical imagining with machine learning techniques. Previously, I completed a Research Software Engineer placement, contributing to software solutions across academic projects.

SDE RTP Project Title: GPU Platform and Hybrid Cloud Deployment with ARO

Project Summary: To design and implement a secure, scalable hybrid cloud infrastructure to support GPU intensive research workflows. This infrastructure will integrate on premise and cloud-based components to meet the computational demands for enabling data processing, AI model training, and secure analytics within a TRE framework. 

As part of the data infrastructure team, my role involves contributing to architecture design, investigating automation tools like Terraform, ensuring secure access and resource management, and aligning the deployment with SDE principles such as isolation, encryption, and auditability. The project also supports broader goals of interoperability, federation readiness, and compliance with national data governance standards. 

Reflections on SDE Skillshub Project Support: So far, I have engaged in a wide range of activities including attending the 2025 TRE Community Conference, completing network and cloud infrastructure training, and contributing to internal infrastructure tasks like configuring GitHub Actions and implementing open-source license scanning using FOSSA. I have also written reports on SDE frameworks and participated in discussions on eLab and NCRI; and upcoming ARO GPU hybrid cloud deployment. 

I am gaining confidence working with tools like Terraform, GitHub Actions, and Visual Studio Code. My manager and colleagues have been incredibly supportive, guiding me through new concepts, helping me troubleshoot, and encouraging me to solve problems independently. This feedback and regular check ins have helped me develop both technically and professionally. 

Whilst there is a lot to learn, particularly in areas like networking and cloud infrastructure, the mix of technical training, meetings, and exposure to real project requirements has given me a clear sense of direction to build the skills needed for future roles in DevOps and cloud engineering. 

How the SDE Team Development hub’s RTP trainee scheme will help achieve your career objectives: The scheme provides a structured and supportive environment that aligns well with my career aspirations in cloud engineering with DevOps. Through formal training, I am gaining foundational knowledge in cloud platforms, IaC, networking, and automation. Regular mentoring offers valuable guidance and practical advice, helping me apply learnings in real world settings. 

Exposure to key technologies such as CI/CD pipelines, hybrid cloud deployments and SDEs is helping me develop hands on experience with the tools and frameworks I aim to use in my future roles. Additionally, participation in meetings, code reviews, and conferences has deepened my understanding of the wider data infrastructure landscape.  Overall, the SDE RTP scheme is building both my technical capability and professional confidence, setting a strong foundation for my long-term career goals in secure and scalable research infrastructure. 

Saurav Sudhar

Institution: Lancashire Teaching Hospitals

Biography: I have always been interested in using technology to improve healthcare/systems. During my undergraduate studies, I developed a deep learning model for diabetic retinopathy detection, which strengthened this interest and introduced me to the real-world potential of AI in medical applications. I then completed an MSc in Data Science & Analytics: projects such as industrial accident report analysis using natural language processing further developed my skills in applying data-driven methods to complex problems. I am particularly motivated by the use of open-source software to build scalable, transparent, impactful solutions for healthcare. In addition, my experience as a software engineer developing web applications has enhanced my practical skills in programming, systems design, and collaborative development.

SDE RTP Project Title: Karectl

Project Summary: I am working on Karectl, a SATRE-compliant Trusted Research Environment (TRE) implementation on Kubernetes, developed as part of the DARE-UK initiative. As a software/infrastructure engineer, I am part of the team building both the TRE infrastructure and the applications within it. The project focuses on developing secure, open-source, and reproducible infrastructure to support collaborative research. Its goal is to make the deployment and maintenance of TREs more efficient, scalable, and community-driven, enabling researchers to access and analyse data safely and responsibly.

Reflections on SDE Skillshub Project Support: The RTP trainee scheme has given me the opportunity to work closely with a team of engineers who have strong technical knowledge and real-world experience in building and maintaining secure infrastructures. This enabl es me to learn how tools and technologies such as Kubernetes, Terraform, Azure are applied in practice, which is far more valuable than learning the theory alone.

Through the scheme, I am also encouraged to take part in training courses, conferences and professional certifications, which is helping me to build a stronger technical foundation and a clearer career direction. The guidance and mentorship from experienced colleagues have been invaluable, giving me insight into best practices and industry standards.

How the SDE Team Development hub’s RTP trainee scheme will help achieve your career objectives: Overall, the scheme is helping me develop both the technical and professional skills I need to progress in my career as a cloud and infrastructure engineer, with a focus on open-source technologies and secure, scalable systems for healthcare research.