At a Glance
- Tasks: Conduct exploratory research and design experiments in AI and machine learning.
- Company: Join Google, a leader in tech innovation and research.
- Benefits: Enjoy a collaborative work environment with opportunities for remote work and professional growth.
- Why this job: Make a real-world impact while contributing to cutting-edge research and technology.
- Qualifications: PhD in Computer Science or related field; experience in machine learning and programming languages preferred.
- Other info: Be part of a diverse team committed to equal opportunity and inclusion.
The predicted salary is between 43200 - 72000 £ per year.
Research Scientist, Paradigms of Intelligence
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corporate_fare Google place London, UK
Mid
Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.
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- PhD degree in Computer Science, a related field, or equivalent practical experience.
- One or more scientific publications in top-tier conferences or journals.
Preferred qualifications:
- First-authored publications in the fields of machine learning (e.g. ICLR, ICML, NeurIPS) or programming languages theory (e.g. PLDI, ICFP).
- Experience in the field of machine learning.
- Experience in the field of programming languages (e.g. lambda calculus, type theory, combinatory logic).
- Experience in the field of automated code discovery (LLM-based, AutoML, evolutionary, or meta-learning-based).
- Experience with post-doctoral research.
About the job
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.
About the job
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.
The team you will be joining conducts basic research into alternative computational AI paradigms beyond those currently trending. We aim to deepen our understanding of how complexity emerges in differentiable/non-differentiable automated algorithm discovery methods. These methods automatically produce computer code that solves given tasks, which are often represented as a collection of data examples. We are particularly interested in finding solutions that exhibit compositionality, hierarchical structures, and component reuse. In your role, you’ll research, develop, and publish findings on novel code representations for discovering such algorithms.
Responsibilities
- Carry out sustained exploratory research.
- Review literature, identify key questions, design experiments, and interpret results.
- Collaborate in person and remotely; maintain a respectful work environment.
- Share ideas verbally and in writing; publish and present work at journals or scientific conferences.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google\’s EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
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Research Scientist, Paradigms of Intelligence employer: Google Inc.
Contact Detail:
Google Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist, Paradigms of Intelligence
✨Tip Number 1
Engage with the research community by attending conferences like NeurIPS or ICML. Networking with other researchers can lead to collaborations and insights that will strengthen your application.
✨Tip Number 2
Showcase your expertise in machine learning and programming languages through online platforms. Contributing to open-source projects or publishing articles on relevant topics can demonstrate your knowledge and passion.
✨Tip Number 3
Prepare to discuss your previous research in detail during interviews. Be ready to explain your methodologies, findings, and how they relate to the role at StudySmarter, particularly in automated code discovery.
✨Tip Number 4
Familiarise yourself with the latest trends in AI and computational paradigms. Being well-versed in current research will not only help you in interviews but also show your commitment to staying at the forefront of the field.
We think you need these skills to ace Research Scientist, Paradigms of Intelligence
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD in Computer Science and any relevant experience in machine learning or programming languages. Emphasise your publications, especially if you have first-authored papers in top-tier conferences.
Craft a Strong Cover Letter: In your cover letter, express your passion for research and how your background aligns with the role. Mention specific projects or experiences that demonstrate your expertise in automated code discovery and your ability to mentor junior team members.
Showcase Your Research Experience: Detail your post-doctoral research experience and any collaborative projects you've been involved in. Highlight your contributions to the research community, including publications and presentations at scientific conferences.
Proofread and Edit: Before submitting your application, thoroughly proofread your documents. Ensure there are no grammatical errors and that your ideas are clearly articulated. A polished application reflects your attention to detail and professionalism.
How to prepare for a job interview at Google Inc.
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail, especially those related to machine learning and programming languages. Highlight any first-authored publications and the impact of your work on the field.
✨Demonstrate Problem-Solving Skills
Expect to face technical questions that assess your problem-solving abilities. Practice explaining your thought process clearly and logically, as this will showcase your analytical skills and how you approach complex challenges.
✨Engage with the Team's Goals
Familiarise yourself with the specific research areas the team is focusing on, such as alternative computational AI paradigms. Be ready to discuss how your expertise aligns with their goals and how you can contribute to their ongoing projects.
✨Prepare for Collaborative Scenarios
Since collaboration is key in this role, be ready to share examples of how you've successfully worked in teams. Discuss your experience mentoring junior members and how you maintain a respectful and productive work environment.