At a Glance
- Tasks: Dive into cutting-edge AI research and develop innovative financial reasoning models.
- Company: Join Deep Insight Labs, a leader in applied AI for investment research.
- Benefits: Gain mentorship, access to resources, and co-author top-tier publications.
- Why this job: Make a real impact by translating research into production-ready AI solutions.
- Qualifications: Master’s/PhD students with a strong foundation in machine learning and Python.
- Other info: Fast-paced environment with opportunities for growth and real-world applications.
The predicted salary is between 500 - 1500 £ per month.
Deep Insight Labs is an applied AI research company building agentic AI systems for investment research and financial reasoning. Our flagship platform, Vector, combines large language models, structured knowledge representations, and human-in-the-loop reasoning to solve complex, real-world analytical problems faced by investors and financial professionals. We operate at the intersection of cutting-edge AI research and production-grade systems, with active efforts to publish in top-tier ML conferences and journals while deploying novel models into real products.
We are seeking a highly motivated Master’s student in Computer Science (or related field) for a research and development internship. The intern will work on novel methods at the intersection of knowledge graphs, representation learning, and LLM-based reasoning, with joint supervision from Deep Insight Labs and Zhongtian Sun, Assistant Professor in AI (MILA, Cambridge, Oxford, University of Kent). This internship is designed for candidates who are serious about research excellence and want to see their work both published and deployed.
Research Focus
- Financial knowledge graph modeling (entities, events, relationships)
- Graph neural networks (GNNs) and representation learning
- Temporal and heterogeneous graphs
- Learning structured representations from unstructured financial text
- Joint embedding of graphs, documents, and numerical signals
- Contrastive and self-supervised learning approaches
- Financial Reasoning with LLMs
- Multi-step reasoning and planning with LLMs
- Integrating symbolic structures (graphs, rules) with neural models
- Explainability, attribution, and reasoning traceability
- Translating research ideas into production-ready models
- Evaluating models under real-world constraints (latency, robustness)
- Building experimental pipelines and benchmarks
Expected Outcomes
- Submission to a top-tier venue (e.g. NeurIPS, ICML, ICLR, KDD, WWW, or leading journals)
- Production deployment of research ideas into Deep Insight Labs’ platform
- Open-source contributions (where appropriate)
Who Should Apply
- Are currently pursuing a Master’s degree/PhD in Computer Science, AI, or related field
- Have strong foundations in machine learning and deep learning
- Are comfortable with Python and at least one ML framework (PyTorch preferred)
- Have prior exposure to NLP, graphs, or representation learning (coursework or projects)
- Are interested in bridging theory and practice
- Can work independently and communicate research ideas clearly
Nice to Have (but not required)
- Experience with knowledge graphs or GNNs
- Familiarity with LLMs and prompting / fine-tuning techniques
- Prior research experience or publications
- Interest in finance or economic reasoning
What We Offer
- Joint academic–industry supervision
- Direct mentorship on research framing, experimentation, and writing
- Opportunity to co-author a top-tier publication
- Experience deploying novel AI models into production
- Access to compute resources and proprietary datasets
- A fast-moving, research-driven environment with real-world impact
Research Internship 2026 (Masters\'/PhD) in Cambridge employer: Deep Insight Labs
Contact Detail:
Deep Insight Labs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Internship 2026 (Masters\'/PhD) in Cambridge
✨Tip Number 1
Network like a pro! Reach out to professionals in the field through LinkedIn or relevant forums. Don’t be shy—ask them about their experiences and any advice they might have for someone looking to break into research internships.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning, NLP, or financial reasoning. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common interview questions related to AI and machine learning, and be ready to discuss your past projects in detail.
✨Tip Number 4
Apply through our website! We’re always on the lookout for passionate candidates. Make sure to tailor your application to highlight how your interests align with our research focus at Deep Insight Labs.
We think you need these skills to ace Research Internship 2026 (Masters\'/PhD) in Cambridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the internship. Highlight any relevant coursework, projects, or research that showcases your understanding of machine learning, deep learning, and financial reasoning.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about this internship and how your background makes you a great fit. Don’t forget to mention any specific interests in financial reasoning or AI that relate to our work at Deep Insight Labs.
Showcase Your Projects: If you've worked on any projects involving NLP, graphs, or representation learning, make sure to include them in your application. We love seeing practical applications of your skills, so share links to your GitHub or any publications if you have them!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we can’t wait to see what you bring to the table!
How to prepare for a job interview at Deep Insight Labs
✨Know Your Stuff
Make sure you brush up on your knowledge of financial reasoning, large language models, and knowledge graphs. Be ready to discuss how your academic background and projects relate to the internship role. This shows you're not just interested in the position but also understand its core requirements.
✨Showcase Your Projects
Prepare to talk about any relevant projects or coursework you've completed, especially those involving machine learning, deep learning, or NLP. Highlight specific challenges you faced and how you overcame them. This will demonstrate your problem-solving skills and practical experience.
✨Ask Insightful Questions
Come prepared with questions that show your genuine interest in the company and the role. Inquire about their current research projects, the technologies they use, or how they integrate academic research into their products. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
✨Communicate Clearly
During the interview, focus on articulating your thoughts clearly and concisely. Practice explaining complex concepts in simple terms, as this is crucial for collaborating with both technical and non-technical team members. Good communication can set you apart from other candidates.