Research Scientist: Hierarchical Sensorimotor Perception

Astera Institute; California; On-site; USD 150,000 - 300,000; Full time

Benefits offered by this job

Collaborative culture

Focus on fundamental research

No revenue pressure

Job summary

Astera Institute in California seeks innovative thinkers for a role focused on developing foundational principles of Artificial General Intelligence (AGI). Candidates will engage in fundamental research, collaborating cross-disciplinarily while prioritizing openness and ethical contributions to science.

The ideal applicant will possess advanced expertise in deep learning frameworks and theoretical knowledge essential for progressing AGI technology. The position offers generous compensation without the constraints of conventional revenue pressures.

Qualifications

• Expert-level skills in deep learning frameworks.
• Strong foundations in theoretical concepts.
• A genuine passion for exploring computational principles of the brain.

Responsibilities

• Develop bi-directional architectures for hierarchical perception.
• Design experiments for out-of-distribution generalization.
• Collaborate with neuroscientists and engineers on scalable systems.

Skills

Deep learning frameworks (PyTorch/JAX)

Graphical models

Information theory

Education

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

Job description

Position Summary

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 Hierarchical Perception: Develop and implement new bi-directional/recurrent architectures for hierarchical perception. These models are expected to provide flexible querying, dynamically variable levels of abstraction, and representations that support planning/reasoning.
• Evaluation and Benchmarks: Design experiments to test and benchmark against existing architectures for out-of-distribution generalization.
• 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.

Compensation Range: $150K - $300K