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채용Google DeepMind

Research Scientist, Generative Modelling for Materials and Chemistry

Google DeepMind

Research Scientist, Generative Modelling for Materials and Chemistry

Google DeepMind

London, UK

·

On-site

·

Full-time

·

1d ago

At Google Deep Mind, 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

Join a multidisciplinary team building state-of-the-art generative models in chemistry & materials to accelerate scientific breakthroughs.

About Us

Science is at the heart of everything we do at Google Deep Mind. From the beginning, we took inspiration from science to build better algorithms, and now, we use our toolkit to accelerate scientific discovery. By bringing together specialists with backgrounds in machine learning, computer science, physics, chemistry, biology and more, we’re optimistic that we can build new methods that will push the boundaries of what is possible and help solve the biggest problems facing humanity.

The Role

As a Research Scientist in our Science unit, you will be at the forefront of applying generative AI to the "Grand Challenge" of predicting the structure and properties of complex matter. You will build foundation models able to navigate vast chemical spaces, moving beyond traditional simulation to direct, high-speed prediction. Your work will bridge the gap between in silico modeling and real-world laboratory discovery, particularly in areas where traditional computational methods are bottlenecked by time and complexity. You will hill-climb evals that represent real-world applications using a problem focused approach, careful experimentation, and the latest technology in AI.

Key responsibilities:

  • Design and train advanced AI models (transformers, generative models, etc.) to model the structure and properties of complex physical systems.
  • Develop deep understanding of scientific domains that can be used to identify novel modelling approaches.
  • Design and execute robust ML experiments that allow for the accumulation of small improvements, sharing results through clear verbal and written communication.
  • Collaborate with other scientists and engineers to help shape the research roadmap.

About You

You are fascinated by the intersection of AI and natural science and determined to help solve grand challenges facing humanity. In order to set you up for success as a Research Scientist at Google Deep Mind, we look for the following skills and experience:

  • PhD / equivalent experience in computer science, computational chemistry, materials science, physics with a focus on atomistic simulation or structural biology.
  • Fluency in generative models and transformers
  • Excellent collaboration and communication skills
  • Experience with modern deep learning frameworks

In addition, the following would be an advantage:

  • Record of high-impact published work at the intersection of AI and natural science, particularly chemistry and materials science.
  • Demonstrated experience in geometric deep learning.

Applications close on Monday 20th April at 5pm BST

총 조회수

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총 지원 클릭 수

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모의 지원자 수

0

스크랩

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Google DeepMind 소개

Google DeepMind

DeepMind Technologies Limited, trading as Google DeepMind or simply DeepMind, is a British-American artificial intelligence research laboratory which serves as a subsidiary of Alphabet Inc.

1,001-5,000

직원 수

London

본사 위치

리뷰

3.8

10개 리뷰

워라밸

3.8

보상

4.2

문화

3.5

커리어

4.0

경영진

2.8

68%

친구에게 추천

장점

Smart and brilliant colleagues

Good compensation and benefits

Work flexibility and remote options

단점

Poor management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and goals

면접 경험

5개 면접

난이도

3.0

/ 5

소요 기간

21-35주

합격률

60%

경험

긍정 60%

보통 40%

부정 0%

면접 과정

1

Application Review

2

Phone Screen/Online Assessment

3

Technical Interview

4

Team Matching Interview

5

Offer

자주 나오는 질문

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Research Experience

System Design