The Monq Fellowship Programme

Current undergraduate (senior year), master's, or PhD student at Princeton, Oxford, Harvard, Bilkent, Sabanci, Koc or METU. Recent graduates (within 2 years) from these institutions Minimum GPA: 3.7/4.0 (or equivalent: First Class Honours at Oxford) Strong academic performance in relevant coursework Advanced coursework in machine learning, artificial intelligence, or computer science (for AI track) Programming proficiency in Python, with experience in ML frameworks (PyTorch, TensorFlow) (for AI track) Understanding of transformer architectures and large language models (for AI track) Experience with distributed systems or enterprise software development (preferred for AI track) Strong programming skills in Python and SQL (for Data track) Experience with cloud platforms (AWS, GCP, Azure) and containerisation (for Data track) Knowledge of data pipeline tools (Apache Spark, Kafka, Airflow) (for Data track) Understanding of database systems and data modelling (for Data track) Strong analytical and quantitative skills (for Product track) Experience with business analysis, consulting, or product management (for Product track) Understanding of enterprise software markets and B2B sales cycles (for Product track) Excellent communication and presentation skills (for Product track) Graduate-level coursework in relevant fields (AI, Economics, Operations Research) (for Applied Research track) Research experience with publications or significant projects (for Applied Research track) Strong mathematical background and analytical thinking (for Applied Research track) Experience with experimental design and statistical analysis (for Applied Research track) Exceptional problem-solving abilities and intellectual curiosity Strong communication skills and ability to work with business stakeholders Entrepreneurial mindset and comfort with ambiguity Passion for applying AI to solve real-world business problems

Contribute to autonomous negotiation agent development Develop multi-dimensional optimisation algorithms Build evaluation frameworks for AI agent performance Research and implement novel approaches to multi-agent coordination Design and implement scalable data pipelines Build enterprise-grade integration systems Develop real-time analytics infrastructure Create data governance and security frameworks Conduct market research and competitive analysis Design go-to-market strategies Build business intelligence tools Develop product strategy Research game theory applications to negotiations Develop mechanism design for procurement auctions Economic modelling of AI impact Develop novel approaches to explainable AI