Research Engineer - AlphaFold Improvements
London, UK
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 and benefit humanity.At 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, maternity 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
Our special interdisciplinary team combines the best techniques from deep learning, reinforcement learning and systems neuroscience to build general-purpose learning algorithms. We have already made a number of high profile breakthroughs towards building artificial general intelligence, and we have all the ingredients in place to make further significant progress over the coming year.
The role
To succeed in this role you will need to be passionate about advancing science using machine learning and other computational techniques. You'll join an interdisciplinary team of domain experts, ML researchers and engineers exploring a diverse set of important scientific problems in biology, physics, mathematics and other areas. Our work is organised into several longer-term focus areas which aim to achieve step changes to the state-of-the-art (as exemplified in AlphaFold). You'll leverage our unique mix of expertise, data and computational resources to experiment and iterate both rapidly and at scale.
As an embedded Research Engineer you will collaborate with researchers and software engineers to develop and run experiments exploring new applications of AI to science problems. The team is pioneering in many different domains so you may take part in exploratory work validating early ideas or work in a maturing area to deepen and exploit a promising line of research. You may also contribute to the scientific knowledge and experience of the team with your own scientific domain knowledge. You will work with internal and external researchers on pioneering research bridging AI and science.
Key responsibilities:
- Plan and perform rapid prototyping of machine learning techniques applied to problems in science.
- Undertake exploratory analysis to inform experimentation and research directions.
- Make improvements to model architectures and training procedures of machine learning models.
- Implement tools, libraries and frameworks to speed up and enable new research.
- Report and present software developments, experimental results and data analysis clearly and efficiently.
- Collaborate with internal and external scientific domain experts.
The role will suit candidates who enjoy working in a heavily experimental setting with large and noisy datasets and who wish to immerse themselves in innovative science, ML and AI research.
About you
In order to set you up for success as a Research Engineer at DeepMind, we look for the following skills and experience:
- Masters degree in computer science, electrical engineering, science, mathematics or equivalent experience.
- Applied experience with machine learning, preferably modern deep learning architectures (e.g. Transformers, CNNs, LSTMs).
- Experience with at least one programming language (with a preference for those commonly used in machine learning or scientific computing such as Python or C++).
- Familiarity and experience with at least one of the following: TensorFlow, PyTorch, Jax, NumPy, Pandas or similar ML/scientific libraries.
- Knowledge of linear algebra, calculus and statistics equivalent to at least first-year university coursework.
- Experience exploring, analysing and visualising data.
In addition, the following would be an advantage:
- Experience working with large and noisy datasets.
- Experience collaborating across fields.
- Nice to have: Scientific knowledge (particularly biology, chemistry and physics).
When assessing technical background we will take a holistic view of the mix of scientific, ML and computational experience. We do not expect you to be an expert in all fields simultaneously. However, except for scientific knowledge, since the role serves as a bridge between all three, some experience in each is necessary. Candidates with particularly strong programming experience and less ML are encouraged to consider our Software Engineering role in the Science team.
What we offer
At DeepMind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options. We strive to continually improve our working environment, and provide you with excellent facilities such as healthy food, an on-site gym, faith rooms, terraces etc.
We are also open to relocating candidates to London and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility).
Competitive salary applies.
Application Deadline: 16th June 2022
Tags: Biology Chemistry Computer Science Data analysis Deep Learning Engineering Linear algebra Machine Learning Mathematics ML models NumPy Pandas Physics Prototyping Python PyTorch Research Statistics TensorFlow Transformers
Perks/benefits: Career development Competitive pay Fitness / gym Flex hours Health care Insurance Medical leave Parental leave
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