Research Scientist, Paradigms of Intelligence
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Minimum qualifications:
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- One or more scientific publication submissions for conferences, journals, or public repositories.
Preferred qualifications:
- Experience with logic circuits/digital electronics.
- Experience with first-authored publications in conferences or journals in physics (e.g., Physical Review Letters), programming languages (e.g., PLDI, ICFP), combinatorial optimization, or especially machine learning (e.g., ICLR, ICML, NeurIPS).
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.
To advance the field of artificial intelligence by exploring alternative computational paradigms beyond those currently trending. We aim to deepen our understanding of how complexity emerges in differentiable/non-differentiable automated algorithm discovery methods. We are interested in the design of systems that, starting from a problem description, are capable of producing algorithmic solutions that exhibit compositionality, hierarchical structures, and component reuse.Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.
Responsibilities
- Own mission programming languages theory (e.g., rewriting systems, type systems, functional programming/physics of complex systems/relevant areas of combinatorial optimization).
- Manage modern machine learning techniques (e.g., deep learning, reinforcement learning, evolutionary computation).
- Review literature, identify key questions, think creatively, iterate on experiments, employ scientific excellence, and publish papers.
- Dive into a project for an extended period of time with excellent coding.
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