Research Fellow

Posted 74ds ago

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Job Description

Research Fellow at FirstPrinciples developing cutting-edge AI Physicist for theoretical research. Engaging deeply with advanced AI and physics through innovative methods and collaboration.

Responsibilities:

  • Improve Theo’s ability to produce scientifically sound, high-quality outputs in 2026;
  • Introduce new ideas, methods, and approaches that meaningfully shift system performance;
  • Bring deep domain expertise (PhD+ level) in one or more targeted research areas.
  • Research, design, and test novel model architectures that combine academic literature, NLP, symbolic reasoning, and structured scientific workflows.
  • Prototype and build embedding representations for physical concepts, mathematical objects, and logical structures, enabling models to reason over equations, abstractions, and scientific constraints rather than surface text alone.
  • Investigate alternatives to transformer-based architectures and deliver concrete recommendations.
  • Design and run targeted experiments to evaluate new architectural ideas, using empirical results to guide the development of next-generation model architectures.
  • Develop reinforcement learning loops that enable models to run internal and independent thought experiments.
  • Design and automate scalable data ingestion pipelines that aggregate scientific literature, metadata, equations, and experimental data.
  • Create custom benchmarks to measure physical understanding, mathematical reasoning, and failure modes in scientific reasoning and abstraction.
  • Refine and release curated datasets and baselines once internal validation is complete.
  • Run and track model training jobs while managing compute usage and budget constraints.
  • Design sandbox environments for controlled autonomous exploration.
  • Build evaluation frameworks using visual and statistical tools to identify strengths and blind spots.
  • Implement tests and guardrails that flag low-quality or unsafe outputs.
  • Maintain internal issue tracking with clear failure modes and fixes.
  • Work closely with engineers to ensure research is feasible and production-ready.
  • Communicate technical trade-offs clearly to non-technical stakeholders.
  • Present regular research updates tied to defined milestones.

Requirements:

  • PhD or postdoctoral researchers in Computer Science, Machine Learning, Theoretical Physics, or a closely related field.
  • Track record of research in either:
  • model architectures, representation learning, or reasoning systems (CS/ML path); or
  • mathematical, physical, or formal reasoning applied to fundamental problems (physics path).
  • Demonstrated ability to translate abstract theory into testable computational systems.
  • Comfortable working across disciplinary boundaries.

Benefits:

  • Fixed stipend for the full term
  • Fully remote