Job Research Scientist AI for Sustainability en Remote

DeepMind en Remote

Digital job Research Scientist AI for Sustainability at DeepMind

Research Scientist AI for Sustainability

DeepMind Remote

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Remote Full-time
Development 2-5 años Software Technical Lead Training
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Job description

*Cambridge, MA is also a location option

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Snapshot

At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Our team is part of the Sustainability Program, whose aim is to revolutionize environmental sustainability with AI. We conduct fundamental research which develops novel AI methods, and we translate our research advances into real-world applications and products. This role focuses on weather and climate, and the connections to energy, water, nature, and other key sustainability domains.

About Us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

Research Scientists at Google DeepMind lead our efforts in developing novel algorithmic methods that push the frontier of AI and its applications.

We are looking for creative thinkers with strong algorithm-design and programming skills, with expertise in and passion for environmental sustainability, and with the potential for leadership in shaping the direction of our Sustainability Program. Previous technical experience with machine learning architectures, learned simulation, fluid dynamics, complex systems, combinatorial optimization, probabilistic modeling, and domain expertise in relevant sustainability problems are valued.

Key responsibilities:

  • Design, implement and evaluate models and software prototypes for sustainability-related problems.
  • Report and present research findings and developments clearly and efficiently, both internally and externally.
  • Contribute to team collaborations to meet ambitious research goals.
  • Engage with application and product needs, to inform research decisions.
  • Able to devise and execute independent research directions.

About You

In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:

  • PhD or equivalent experience in machine learning, artificial intelligence, computer science, or comparable technical domain.
  • A proven track record of publications in top-tier conferences and/or journals.
  • Strong background in machine learning foundations (esp. supervised learning, probabilistic modeling, graph-based learning, and/or optimization).
  • Experience with deep learning platforms.
  • Familiarity with distributed systems and training / inference infrastructures.
  • Commitment/experience/expertise in weather/environmental sustainability and/or allied areas (e.g., fluid dynamics, complex systems, combinatorial optimization, remote sensing).
  • Potential for leadership in identifying, planning, and executing key research directions, and/or managing teams.

In addition, the following would be an advantage:

  • Core contributor to OSS projects.
  • Experience with JAX and its ecosystem.
  • Experience with remote sensing data.
  • Experience translating research innovations into product applications.
  • Experience with leadership (academic and/or industry).

 



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