Our commitment to research

Posted on: 25 September 2024 in Meet our Team

Hear directly from one of our summer interns about our Research IT summer internship programme.

As part of IT Services ongoing commitment to supporting University of Liverpool researchers, we are thrilled to announce the successful completion of the N8 Centre of Excellence in Computationally Intensive Research (N8 CIR) Summer Internship Programme. 

Aradhya Tripathi, Wanrong Yang, Chi Xing, and Ramandeep Kang joined our IT Research Division to contribute to impactful research projects across three key themes: Digital Health, Digital Humanities, and Machine Learning. 

Over the course of 12 weeks (full-time) or 21 weeks (part-time), the interns worked closely with University academics and Research IT staff to tackle short-term projects. These projects not only advanced their understanding of computational research but also addressed real-world academic challenges. 

The interns, selected through a rigorous application process, received comprehensive training in high-performance computing platforms, GPU technology, and modern coding languages such as C++, Python, and R. This intensive training empowered them to confidently execute their research projects and grow as future leaders in the research computing community. 

In addition to providing the interns with valuable hands-on experience, this programme offered a crucial opportunity for academics who often face difficulties in finding qualified candidates and securing funding for short-term research initiatives. 

We are lucky enough to have one of our intern’s Chi Xing share his experience, here’s a few questions we asked him about how it went.

1. What’s the most important skill or lesson you’ve learned during your time with the Research IT team? 

The most important lesson I’ve learned is how to effectively evaluate and benchmark large language models, specifically in their ability to process and understand complex biological literature. This experience has not only deepened my technical expertise but also taught me how to critically assess the performance of various AI tools in real world application. 

2. In what ways did the internship experience challenge your problem-solving or analytical skills? 

The internship required me to approach problems with a multi-faceted view. I had to analyse various models, compare their performances, and identify potential biases or limitations. This pushed me to think critically and methodically. 

3. Were there any aspects of IT services or research technology that you found particularly surprising or different from what you expected? 

I was surprised by the abundance of computing resources available to the Research IT Team. My internship tasks are computationally intensive, and a lot of computational resources are necessary. I was also honored to experience one of the world's best AI processors, the GH200 from NVIDIA, which impressed me. 

4. Did you have opportunity to suggest new ideas or improvements to existing processes? How were your suggestions received? 

Yes, I had the chance to suggest enhancements to the benchmarking workflow, such as an objective scoring system and some methods for reducing input size. My suggestions were welcomed and has been developed and released. 

5. If you could propose one innovation or improvement to the IT Services Research team based on your experience, what would it be and why? 

I think it's fantastic in all respects, and it would be great to have more computing resources to accelerate our research. Even though we now have abundant computational resources, inference for LLMs is still very time-consuming, so perhaps our research would be accelerated if we used better and more processors. 

6. If you had the chance to redo any part of your internship, is there anything you would approach differently? 

If I could redo any part, I would focus more on understanding the biological literature in greater depth before diving into benchmarking. A deeper understanding of the domain would have helped me contextualize model performance better and might have led to more insightful analyses. 

7. How do you plan to apply the skills and knowledge you’ve gained in your future studies or career? 

The skills I’ve gained—such as model evaluation, critical thinking, and interdisciplinary collaboration—are invaluable for my future. Whether I pursue further studies or a career in AI or computational biology, these skills will help me tackle complex problems. 

8. How did your internship experience help shape your understanding of the professional IT environment? 

My internship gave me a strong understanding of the work of the Research IT Team. I learned that IT is not just about technical support but also about fostering innovation, enabling research, and directly contributing to scientific advancements through technology. 

9. What advice would you give to future interns joining the Research IT team? 

Be open to learning from both the technical and research sides, as this will give you a more holistic understanding of the challenges and solutions in the field. Don’t hesitate to ask questions and suggest ideas—this team values creativity and collaboration, everyone in this team is fantastic!