Research Scientist, Machine Learning and Neuroscience

Minimum qualifications:

• PhD degree in Computer Science, a related field, or equivalent practical experience.
  
• One or more scientific publication submission(s) for conferences, journals, or public repositories.
  
• Coding experience in Python, JavaScript, R, Java, or C++.
  
• Machine Learning experience.

Preferred qualifications:

• 2 years of coding experience in Python, JavaScript, R, Java, or C++.
  
• 1 year of experience owning and initiating research agendas.
  
• Experience with automated algorithm discovery methods, learning to learn, or program synthesis.
• Experience with digital hardware or hardware intended for machine learning.
• Knowledge of computational neuroscience.
• Familiarity with non-gradient-based optimization techniques.

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.

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.

• Explore thoroughly into a project for an extended period of time.
  
• Design, execute, and interpret machine learning experiments, selecting appropriate algorithms, models, and evaluation metrics.
• Review literature, identify key questions, think creatively, iterate on experiments, and employ scientific accuracy.
• Be proficient in one or more modern programming languages (e.g., Python), learn new programming languages. Learn technologies such as large-scale computation methods, be experienced with one or more machine learning libraries (e.g., JAX or PyTorch).
• Write clear academic papers, give formal research talks, and have informal discussions with colleagues.