Research Assistantship

About the Company

We are an Intelligent Computing company operating at the forefront of Artificial General Intelligence Research and Development. Our mission is to build the perfect tools for the Human Mind. Ren is pioneering a new approach to building intelligent computing systems, based on an entirely new framework for Machine Learning called the Universal State Machine (USM). The USM enables a new kind of intelligent system; one that is not built on the primitives of Deep Learning, and does not come with its inherent limitations.

The Opportunity

The Universal State Machine development is a completely novel computational architecture, it is not being pursued by any other labs or companies. This makes this assistantship the only place on earth where this specific opportunity is available.

As a Research Assistant, you will report directly to the CEO, Rukmal Weerawarana. You will work in tandem with our main Engineering team. Your primary goal is to formalize and spearhead the research of the mathematics underlying the Universal State Machine, translating our physical and computational breakthroughs into rigorous mathematical proofs. To accelerate your work, you will have full access to the suite of tools, modules, and infrastructure developed by our internal engineers.

Initial Deliverables and Research Goals

You will spearhead the effort to formalize the theoretical underpinnings of our technology. The following deliverables build on one another from a research perspective:

• Core Formulation: Establish the formal mathematical formulation of the Universal State Machine.
• Topological & Quantum Dynamics: Formalize the scientific evaluation of the USM as a Topological Quantum Automaton. You will rigorously define how the USM acts as a Classical Emulator of Open Quantum Dynamics.
• Topological Renormalization: Prove that our calibration operation consistently reaches a stable fixed point across arbitrary observation sets, heavily utilizing Dynamical Systems and Graph Theory.
• Isomorphism Proofs: Mathematically prove the isomorphism between the Universal State Machine synthesis algorithm and the Attention mechanism in the Transformer, utilizing a Path Integral formulation.

Required Technical Capabilities

• Exceptional mathematical background with a focus on Dynamical Systems, Graph Theory, and Set Theory (specifically Transfinite Ordinals).
• A strong grasp of Deep Learning principles and the ability to rethink computing primitives to understand the USM framework.
• Good Software Engineering skills to be able to use our APIs to conduct research and investigation work.
• Strong Machine Learning intuition and experience with scientific programming.
• Well developed reasoning skills, especially around building efficient systems.
• The ability to distill highly abstract technical concepts into clear, actionable plans and formal academic literature.

Required Personal Qualities

• Be excited about and willing to work incredibly hard to build the next generation of Artificial Intelligence.
• Be engaged and motivated by very hard technical challenges.
• A preference for learning and mastering new frameworks over relying on established industry norms.
• Incredibly high attention to detail.
• A drive for great craftsmanship and an intolerance for technical mediocrity.

Ideal Candidate

• Advanced degree in Physics, Mathematics, Statistics, Financial Engineering, Computer Science, or another quantitative field.
• Proven track record of conducting and publishing research in your domain.
• Experience working with new data modalities, and finding needles in haystacks.
• Deep understanding of multi-state and multi-scale systems mediated by Complex-valued state vectors.
• Thrives in a high-agency environment with a lot of freedom to create and explore.

Logistics & Benefits

• Location: You will be working in-person at the Ren Asia offices in Port City, Colombo.
• A vibrant, fast-paced working environment with smart colleagues.
• In-office lunch and dinner + transportation benefits for late nights at the office.