Why did you decide to study this Masters course at Sussex?
Before pursuing my MRes at Sussex, I completed a BTech (Bachelors) and an MTech (Masters) in computer science and engineering in India.
I then worked as a data scientist, developing customised machine learning (ML) models and a drone path-planning algorithm.
While my role was industry-based, the work was inherently research-driven, which gradually sparked a deep interest in research. That curiosity pushed me to explore postgraduate opportunities to broaden my knowledge in artificial intelligence (AI) and contribute meaningfully to the field through research.
Though I originally wanted to pursue a PhD, I wanted to gain some experience with what research is like and how it is used in industry to shape ideas in the real world.
After a lot of searching, Sussex stood out for the following reasons:
- Academic specialisation in emerging fields - Sussex's investment in Spiking Neural Networks, a frontier area within computational neuroscience, was a major draw. The bio-inspired AI module offered something rare - the opportunity to gain both theoretical grounding and practical experience in a field at the forefront of AI research. As someone looking to transition from industry into research, this was exactly the kind of intellectual challenge I was seeking.
- The professors made the difference - when evaluating universities, I always looked beyond the course curriculum to the research interests of the faculty. At Sussex, I was genuinely impressed by the depth of expertise in the knowledge base. Knowing I would be guided by researchers actively pushing boundaries made the university feel like the right environment for serious academic growth.
Choosing Sussex was never just about a degree. It was about finding the right ecosystem that is academically, professionally, and personally suitable for me.
What was the application process like?
As an international student, I was initially uncertain about how complex the process might be. However, the Sussex admissions website was very user-friendly. Every document requirement was clearly listed on the application site and well explained. Document uploading was pretty seamless, with easy PDF uploads that left no room for confusion. I was able to complete the entire application with confidence and without seeking external guidance, and that clarity and transparency from the first step made a real difference.
How are you funding your Masters?
My Masters degree is self-funded, which was a significant financial commitment to take on. However, Sussex made that decision more manageable for me through their scholarship opportunities.
I was fortunate to benefit from both the Sussex India Scholarship and the Masters Degree Scholarship, which together provided financial relief and made pursuing this degree a more realistic goal.
Also, knowing that Sussex actively supports international students through such initiatives gave me additional confidence in my choice of university.
Could you tell us a bit about the course and how it is structured and assessed?
In my autumn semester, the curriculum included core modules such as 'Bio-Inspired AI' and 'Advanced ML Techniques'.
What I found new was the flexibility to pair these with an optional subject of my own choice, which is something quite different from postgraduate courses in India, where you are typically given a fixed list of compulsory subjects.
I chose 'Algorithmic Approaches to Mathematics'. We also received structured guidance on writing a research proposal, which was invaluable not just academically but also as a long-term skill every researcher needs.
In the spring semester, there are two modules. 'Applications and Implications of AI' was one of the most engaging subjects, giving space to discuss current AI innovations, their real-world impact, and present our own perspectives, followed by open discussions that were genuinely stimulating. 'Research Methods' covered every dimension of the research process, from how research is conducted and publishing papers to poster-making and understanding academic conferences.
Both modules included hands-on practical sessions, which built my confidence and allowed me to gain different perspectives from peers and professors.
The assessment across the course is entirely coursework-based. Presentations, assignments and a dissertation are the main submissions.
Something I particularly appreciate is the mid-module feedback process, where the professors actively collect class feedback on whether anything needs to be added or whether the teaching style needs adjusting.
Finally, the dissertation is the most intellectually demanding and rewarding part of the journey. Developing a research idea is not only about applying standard techniques; it also requires original thinking and a real contribution to the field.
How does postgraduate life differ from that of an undergraduate?
Back home, student life followed a very structured, pre-planned path, with:
- fixed subjects
- packed schedules
- practical assignments
- exams
- building projects for your profile
- then placements.
Everything was mapped out, and you were essentially expected to follow those steps in order. By the time I considered exploring something beyond that, I was already working as a data science intern.
Many students manage to achieve a great deal within that system, but I tend to focus on one thing at a time. I find that giving my full attention to what is in front of me works better than trying to do everything at once. I always felt I was missing proper, personalised guidance, someone who could help me navigate my own path rather than just pointing me towards a predefined one.
That is where Sussex has made the biggest difference. From the beginning, I have had support at every step, from the admissions team and the Student Centre to my school, my course convenor, my supervisor, and even the professor I am currently working under as a research assistant.
What have you enjoyed most about your Masters course?
Although there are responsibilities and deadlines to meet, as a research student in AI, you are genuinely encouraged to think freely and creatively, and that has been the most liberating and fulfilling part of this entire experience.
Another thing I have really appreciated is the flexibility around optional modules. If you attend a class and realise it isn't the right fit for you, you have the option to switch to a different module that suits you better.
There is a limit to how many times you can do this, but simply having that choice is amazing. We even have these once-a-week AI seminars, where professors from different universities give presentations on their areas of interest or current work, offering exposure to what is currently happening in a particular research area and providing direction for students.
What are your highlights of being a student at Sussex?
Joining the students' union and volunteering as a student representative have been among the most rewarding parts of my time at Sussex. The experience has given me a platform to communicate with other students and develop leadership and teamwork skills. Being part of such an active and diverse community has reinforced my sense of purpose and belonging during my studies.
How is your Masters preparing you for the job market?
Being an MRes student has prepared me well for both academic and industry pathways. On the academic side, the qualification provides a strong foundation for pursuing a PhD.
Beyond that, the course has also equipped me with highly relevant industry skills. In terms of knowledge, I have gained expertise in emerging areas such as spiking neural networks (SNNs), including hands-on experience with tools like the mlGeNN library, as well as an in-depth understanding of large language models (LLMs) and current ML techniques used in industry today.
What support or guidance have you received from the university, and how does it help you?
At Sussex, the careers support has been really important for me. The university runs careers fairs where I can talk directly to employers, learn about their companies and understand what the job market currently looks like. I regularly check the Career Hub for roles that match my interests.
I also found it very thoughtful that there was a specific event focused on career options back home while we're still studying here.
On the academic side, speaking with professors has helped me find mailing lists and networks where PhD and funded research opportunities are advertised.
What are your career ambitions?
My main focus is to find a role in industry, such as an AI/ML engineer, researcher or data scientist, where I can apply my previous experience as a data scientist and the advanced skills I am developing in my MRes.
I am particularly interested in the UK tech sector because the collaborative, innovation-focused work culture I have researched really appeals to me, and I want to learn how high-impact AI products are built in practice.
Further down the line, my goal is to pursue a fully funded PhD in areas such as LLMs or autonomous multi-agent systems, ideally building on the industry experience I gain in my first roles. It would allow me to contribute to both research and real-world applications, while keeping my career rooted in solving meaningful, technically challenging problems.
Beyond my studies, I have also taken on the role of mentoring, something that is very close to my heart. I know from personal experience how much of a difference the right guidance can make, and I believe that access to good mentorship should never be a privilege.
What advice would you give to others considering a Masters in this field?
- Pick a topic you're genuinely interested in for your dissertation or research direction, as it will stay with you for a long time.
- See yourself as a researcher, not just a student.
- Build a good, honest relationship with your supervisor and peers, as you'll get to learn a lot from them.
- Get involved in seminars, career fairs and peer networks for support and future opportunities.
- You're allowed to make mistakes during your programme. Feel free to make them, discuss them openly, learn from them and work calmly towards a solution.
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