Research Scientist, Multimodal Modelling, Foundational Research (Paris, Zurich, or London)
Paris, France
DeepMind
Artificial intelligence could be one of humanity’s most useful inventions. We research and build safe artificial intelligence systems. We're committed to solving intelligence, to advance science...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 seeking a research scientist to join our team dedicated to investigate the development of core multimodal models for healthcare applications. In this role, you will engage in cutting-edge research into vital technologies underpinning next-generation multimodal models, while simultaneously contributing to the exploration of healthcare applications.
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, ensuring that safety and ethics are the highest priority.
The Role
We are seeking a highly motivated Research Scientist, with a strong background in foundational research, to drive the development of next-generation multimodal models and healthcare applications. This will involve close collaboration with research scientists and software engineers across the globe, working to create AI models capable of integrating and reasoning across diverse modalities. At Google DeepMind, our Research Scientists work collaboratively to tackle fundamental challenges in machine learning and AI, pushing the boundaries of what's possible.
Key Responsibilities
- Conduct cutting-edge research and develop novel technologies.
- Design and implement innovative model architectures that effectively integrate diverse datasets, particularly across image and text modalities.
- Develop and establish benchmarks for evaluating multimodal models across a wide range of tasks and domains.
- Clearly communicate research findings and collaborate with teams across Google to maximize impact.
- Contribute effectively within a collaborative environment to achieve ambitious research goals.
About You
To thrive as a Research Scientist at Google DeepMind, we're looking for individuals with the following qualifications and experience:
- A PhD in machine learning, computer science, statistics or a closely related field.
- A strong publication record in top machine learning conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV) and healthcare journals (e.g. Nature Medicine).
- A proven track record of deep learning and experience with Python and neural network training (publications, open-source projects, relevant work experience, …).
- Significant experience in training, evaluating, and interpreting large multimodal models and large language models.
- Ability to communicate technical ideas effectively, e.g. through discussions, whiteboard sessions, written documentation.
- Proven ability to design and execute independent research projects.
In addition, the following would be an advantage:
- A solid understanding of computer vision.
- Experience working with datasets in medical imaging and other healthcare modalities.
Application deadline: 28th February 2025
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Computer Science Computer Vision Deep Learning ICLR ICML LLMs Machine Learning NeurIPS Open Source PhD Python Research Statistics
Perks/benefits: Career development Conferences
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