Research Scientist: Energy Based Models

Astera Institute; Emeryville (CA); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

No pressure to align research with market goals

Direct contribution to AGI knowledge

Collaborative team culture

Job summary

An innovative research startup in Emeryville is looking for a Research Scientist specialized in energy-based models to develop foundational principles for Artificial General Intelligence (AGI). The ideal candidate will lead groundbreaking research, collaborate across disciplines, and contribute to open science while focusing on the core challenges in AGI technology. This role values curiosity and innovation without pressure from market demands, fostering a collaborative and mission-first culture.

Qualifications

• PhD in a relevant field preferred, with consideration for exceptional candidates.
• Strong foundations in concepts like deep learning and information theory.
• Expert-level skills in deep learning frameworks like PyTorch/JAX.

Responsibilities

• Develop new architectures for energy-based world models.
• Design experiments for testing high-level cognition and sensory-motor integration.
• Collaborate with neuroscientists and engineers for scalable systems.

Skills

Deep learning

Graphical models

Information theory

Programming in PyTorch

Research coding

Education

PhD in Computer Science, Electrical Engineering, Neuroscience, Physics, or a related quantitative field

Tools

PyTorch

JAX

Job description

Astera Institute

Research Scientist: Energy based models

About the Role

We are seeking brilliant, unconventional thinkers to join us. In this role, you will not be chasing incremental gains on standard benchmarks. Instead, you will be tasked with developing the foundational principles of Artificial General Intelligence. We believe that understanding the "code of the brain" is the most viable path to building truly intelligent machines, and we are looking for scientists who can bridge the gap between biological intelligence, computational theory, and building at scale.

Core Responsibilities

• Fundamental Research on Energy Based, Hierarchical Latent Variable Models: Develop and implement new architectures and learning/inference algorithms for neuroscience-inspired energy-based world models, with focus on representations that allow for parallel distributed planning.

• Scientific Discovery: Design experiments to test hypotheses regarding high-level cognition, causal representations, sensory-motor integration, active inference, and unsupervised learning.

• Cross-Disciplinary Collaboration: Work alongside neuroscientists and software engineers to translate abstract mathematical frameworks into scalable systems.

• Contribute to Open Science: Help innovate new publication models that incentivize speedy dissemination, open source code releases, free open access, and impact measurements based on uptake.

Desired Qualifications

• Technical Depth: Preferred: PhD in Computer Science, Electrical Engineering, Neuroscience, Physics, or a related quantitative field. We are always open to considering exceptional candidates, even those with non-traditional educational histories.

• Theoretical Rigor: Strong foundations in deep learning, graphical models, and information theory.

• Coding Proficiency: Expert-level skills in deep learning frameworks (PyTorch/JAX), with a focus on clean, reproducible research code.

• AGI Mindset: A demonstrated interest in the "big questions" of AI—robustness, generalization, and common-sense reasoning.

• Curious About the Brain: A genuine passion for exploring the computational and architectural principles of the mammalian brain.

• Startup DNA: Ability to thrive in a lean, fast-paced environment where you have high autonomy and a direct influence on research direction.

Why Join Us?

• We recognize the need for fundamental research: No pressure to align research with quarterly revenue goals, market competition, or product roadmaps. We can focus on solving the core problems and achieving breakthroughs that enable the next generation of AGI technology.

• Mission-First: Your work contributes directly to the global pool of knowledge and the safe development of AGI.

• Collaborative culture: We work in teams, organized around challenge problems and attack paths, without big-company inertia or politics.