Senior Research Scientist, Machine Learning and Neuroscience

Requirements:

• PhD degree in Computer Science, Neuroscience, Mathematics, Physics, a related field, or equivalent practical experience.
• 2 years of experience leading a research agenda and working with other researchers.
• Experience coding in Python, Java, or C++.
• One or more scientific publication submission(s) for conferences, journals, or public repositories, including publications on machine learning or computational neuroscience.

Nice to haves:

• 2 years of experience coding in Python, Java, or C++.
• Experience with automated algorithm discovery methods, meta-learning, or program synthesis.
• Experience with or working knowledge of digital hardware or hardware intended for machine learning.
• Knowledge of computational neuroscience.
• Familiarity with non-gradient-based optimization techniques.

What you'll be doing:

• Author research papers to share and generate impact of research results across functions and in the research community.
• Help in growing research business by sharing research trends and best practices within the community, including disseminating research findings at top research conferences and journals.
• Drive project work by defining the data structure, framework, design, and evaluation metrics for research solution development and implementation. Identify timelines and obtain resources needed.
• Identify new and upcoming research areas by interacting with potential external and internal collaborators. Help in developing long-term research strategy and plans to expand the impact of Google research.
• Identify defined problems/gaps in existing technology and engage stakeholders and leaders to address them. Implement ideas/discoveries as computer code, possibly at data center scale.

Perks and benefits:

• Opportunity to work on real-world problems in various fields of computer science including machine learning, data mining, natural language processing, and more.
• Contribute to the wider research community by sharing and publishing findings.
• Potential to impact technology used by billions of people every day.
• Regular publication in academic journals, open source projects, and application of research to Google products.