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- Tasks: Lead innovative research in AI for weather forecasting and develop practical solutions.
- Company: Join Google DeepMind, a leader in AI research with a mission to improve weather forecasts for humanity.
- Benefits: Enjoy constant learning opportunities, access to cutting-edge technology, and a collaborative work environment.
- Why this job: Make a real impact on society while working with top researchers in a creative and supportive culture.
- Qualifications: PhD in a relevant field, strong ML/statistics knowledge, and experience in weather forecasting required.
- Other info: Diversity is valued; accommodations are available for applicants with disabilities.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Research Scientist, AI for (Sub)seasonal Weather Forecasting
Join to apply for the Research Scientist, AI for (Sub)seasonal Weather Forecasting role at Google DeepMind
Research Scientist, AI for (Sub)seasonal Weather Forecasting
Join to apply for the Research Scientist, AI for (Sub)seasonal Weather Forecasting role at Google DeepMind
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Snapshot
We\’ve built a unique culture and work environment where ambitious, long-term research can flourish and be translated into societal benefits. We\’ve made high-profile breakthroughs for medium-range weather forecasting (e.g., GraphCast, GenCast) and are now extending this work into the 2-week to 3-month (subseasonal) range. We are seeking a Research Scientist to help drive this exciting research.
About Us
Our mission is to create the world’s most trustworthy and useful weather forecasts for the benefit of humanity. Research is central to our mission, but we also ensure that our research can be turned into tangible impact that benefits humanity. Our interdisciplinary team combines the best techniques from machine learning, statistics, and meteorology to build the science for the best weather forecasting systems. Our approach encourages collaboration across all groups within the research team, cultivating ambitious creativity and innovative research.
The Role
Research Scientists are encouraged to lead or support a research agenda that produces practical technological advances in weather forecasting.
The expectation is that research scientists will conduct novel research according to ambitious long-term agendas, while maintaining a strong focus on methods and tools offering practical benefits in the short term as a form of pragmatic grounding. Central to this process is the idea that rapid iteration and refinement of solutions for real-world use cases provides a strong basis for better understanding the frontiers of research in this fast-paced field.
Key responsibilities:
- Contribute (and lead) the ideation and development of new data-driven approaches to (sub)seasonal weather forecasting advised by the current state of research.
- Partner with research engineers to develop ambitious prototypes and design and implement evaluation protocols around these prototypes.
- Identify roadblocks and research challenges by empirically or theoretically studying the failures and limitations of existing methods.
- Develop novel technical or methodological solutions to overcome these obstacles and limitations.
- Help identify, within Google’s broad portfolio of research projects, methods which could be adapted or tried against our evaluations, as well as teams and individuals with which the team could partner to overcome challenges whilst providing grounding and evaluation for that collaborator\’s research agenda.
- Digest and understand complex research papers, theory and practice.
- Own, report and present (verbally and in writing) research developments and experimental results to both the immediate and broader research teams, as well as externally.
- Promote scientific excellence through mentoring and reviewing.
The Team
Our team is especially focused on:
- Machine learning (ML) for weather modelling and forecasting.
- Graph neural networks, diffusion models.
- Scalable Bayesian inference.
- Climate and sustainability-related research.
- A variety of complex problems to work on, with the opportunity to learn constantly through experimentation.
- Access to a team of leading researchers, engineers, and problem solvers to learn from, with the opportunity to contribute your own thinking and specialist knowledge to our mission.
- Constant learning, training, and development opportunities—from technical courses to improving presentation skills—to help you design a career that works best for you.
- Access to leading technology, ever-evolving tech stacks, and Google-scale systems to allow your work to flourish.
- An opportunity to make contributions to addressing societal challenges.
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 degree in a relevant field.
- Proven knowledge of ML and/or statistics, e.g., deep learning.
- Proven experience working on weather forecasting in either an industry or a research lab setting.
- Strong knowledge and experience of Python.
- Working knowledge of Jax, TensorFlow, or similar frameworks.
- Experience with research and publishing, e.g., authored papers.
In addition, the following would be an advantage:
- Experience with simulators, partial differential equations, and/or numerical methods.
- Experience with modelling of other environmental systems (e.g., oceans, sea ice).
- Experience in ML for the physical sciences and/or sustainability.
- Experience with large-scale and/or distributed computing.
Closing date: Wednesday, 20th August at 5:00pm BST
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.
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Research Scientist, AI for (Sub)seasonal Weather Forecasting employer: Google DeepMind
Contact Detail:
Google DeepMind Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist, AI for (Sub)seasonal Weather Forecasting
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, particularly in the context of weather forecasting. Being able to discuss recent breakthroughs like GraphCast or GenCast during your interview will show your genuine interest and understanding of the field.
✨Tip Number 2
Network with professionals in the meteorology and AI sectors. Attend relevant conferences or webinars where you can meet researchers and engineers from Google DeepMind. Building these connections can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss your previous research experiences in detail, especially those related to weather forecasting. Be ready to explain how your work has contributed to practical applications, as this aligns with the role's focus on translating research into societal benefits.
✨Tip Number 4
Showcase your collaborative skills by highlighting any past projects where you worked with interdisciplinary teams. Emphasising your ability to partner with others to overcome challenges will resonate well with the team-oriented culture at Google DeepMind.
We think you need these skills to ace Research Scientist, AI for (Sub)seasonal Weather Forecasting
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, statistics, and weather forecasting. Include specific projects or research that align with the role's requirements.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and weather forecasting. Mention any specific projects or breakthroughs from Google DeepMind that inspire you and explain how your skills can contribute to their mission.
Showcase Your Research Experience: Detail your research experience, especially any publications or papers you've authored. Highlight your familiarity with Python and frameworks like Jax or TensorFlow, as these are crucial for the role.
Prepare for Technical Questions: Anticipate technical questions related to machine learning and weather forecasting during the interview process. Brush up on relevant theories, methodologies, and recent advancements in the field to demonstrate your expertise.
How to prepare for a job interview at Google DeepMind
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail, especially those related to weather forecasting or machine learning. Highlight any publications you've authored and explain how your work contributes to the field.
✨Demonstrate Technical Proficiency
Make sure you can confidently talk about your experience with Python and frameworks like Jax or TensorFlow. Be ready to provide examples of how you've used these tools in your past work, particularly in relation to data-driven approaches.
✨Understand the Company’s Mission
Familiarise yourself with Google DeepMind's mission and recent breakthroughs in weather forecasting. This will help you align your answers with their goals and demonstrate your genuine interest in contributing to their research agenda.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your ability to identify and overcome research challenges. Think of specific examples where you've tackled obstacles in your work and be ready to discuss your thought process and solutions.