Senior Research Scientist, Alternative Computational Paradigms

1 Month ago • 2 Years + • Research & Development • Artificial Intelligence

About the job

Job Description

Google Research is seeking a Senior Research Scientist to join our team focused on exploring alternative computational paradigms beyond those currently trending. The role involves conducting independent research, implementing discoveries as code, collaborating with fellow researchers and engineers, disseminating findings, and contributing to a welcoming environment. The team is particularly interested in discovering learning algorithms for experimental, energy-efficient hardware paradigms, aiming to influence the direction of both hardware and algorithms for AI. This research leverages both hand-design and automated discovery methods, drawing inspiration from neuroscience while primarily targeting artificial hardware, both current and future.
Must have:
  • PhD in Computer Science or related field
  • 2 years of experience leading research
  • Software development experience
  • Publications in machine learning or computational neuroscience
  • Expertise in alternative AI paradigms
Good to have:
  • Experience with automated algorithm discovery methods
  • Social media learning expertise
  • Program synthesis experience
  • Digital hardware or hardware for machine learning experience
  • Computational neuroscience knowledge
  • Familiarity with non-gradient-based optimization techniques
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Minimum qualifications:

  • PhD degree in Computer Science, a related field, or equivalent practical experience.
  • 2 years of experience leading a research agenda.
  • Experience in software development in one or more programming languages.
  • Publication record in machine learning or computational neuroscience, showing relevance to the stated research topic (alternative AI paradigms).

Preferred qualifications:

  • Experience with automated algorithm discovery methods, social media learning, or program synthesis.
  • Experience with or working knowledge of digital hardware or hardware intended for machine learning.
  • Broad or specific knowledge of computational neuroscience.
  • Familiarity with non-gradient-based optimization techniques.

About the job

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

This role focuses on basic, exploratory research. Namely, we seek to advance the field of AI by exploring alternative computational paradigms beyond those currently trending. In particular, our team is interested in the discovery of learning algorithms for experimental, energy efficient hardware paradigms. This way, we aim to influence the direction of both hardware and algorithms for AI. We use both hand-design and automated discovery methods, like Automated ML. We draw inspiration from neuroscience, but our primary goal is to target artificial hardware, current or future.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

The US base salary range for this full-time position is $161,000-$239,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .

Responsibilities

  • Conduct independent, self-driven research on alternative AI paradigms.
  • Implement ideas/discoveries as computer code, possibly at data center scale.
  • Collaborate with fellow researchers and engineers.
  • Disseminate research findings at top research conferences and journals.
  • Help maintain our respectful and welcoming environment.
View Full Job Description
$161.0K - $239.0K/yr (Outscal est.)
$200.0K/yr avg.
Cambridge, Massachusetts, United States

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About The Company

A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.

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