DeepMind

Research Scientist, AI-powered Scientific Discovery

Montreal, Canada
Large Language Models Reinforcement Learning Deep Learning Natural Language Processing JAX TensorFlow PyTorch Machine Learning AI
Description

Research Scientist, AI-powered Scientific Discovery

Location: Montreal, Canada

Department: Frontier AI

Research Scientist, AI-powered scientific discovery

Location: Montreal, Canada

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 opportunities 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

We are looking for a Research Scientist to join our team in Montreal dedicated to AI for Scientific Discovery. Specifically, the team studies systems that combine code execution and retrieval tools with natural-language scientific knowledge to accelerate new scientific discoveries. Research includes, but is not limited to general purpose algorithms that leverage Large Language Model (LLMs) for efficient search and exploration, LLM fine-tuning with Reinforcement Learning, and open-ended tasks for large scale AI-powered empirical research.  

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 architecture towards the end goal of solving and building Artificial General Intelligence.

In this role, responsibilities will include making key contributions into the latest research developed in Google DeepMind Scientific Discovery effort, such as:

Key responsibilities

  • Design, implement and evaluate models, agents and software prototypes of large foundational models.
  • Push the boundary of state of the art RL methods and machine learning optimization methods to build autonomous scientific discovery systems. 
  • Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing.
  • Suggest and engage in team collaborations to meet ambitious research goals.
  • Work with external collaborators and maintain relationships with relevant research labs and key individuals as appropriate.
  • Work in collaboration with our Responsible AI teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity.

About you

You are a passionate and talented researcher with a strong foundation and a proven ability to conduct impactful research in AI. You embrace change and thrive under ambiguity. You have a collaborative mindset and are excited to work as part of a team to tackle ambitious research challenges. You are passionate about seeing your research translated into real-world products that improve the scientific discovery process of users. You are eager to see your research contribute to real-world applications and are driven by a desire to create positive change through AI.

  • PhD in Computer Science, Artificial Intelligence, or a related field.
  • Strong publication record in top-tier machine learning conferences or journals.
  • Solid understanding of deep learning, natural language processing, and/or reinforcement learning.
  • Experience with Large Language Models, preferably in the context of code synthesis.
  • Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch.
  • A real passion for AI!
DeepMind
DeepMind

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