At a Glance
- Tasks: Collaborate on groundbreaking ML solutions for innovative glass storage technology.
- Company: Join a multi-disciplinary team at the forefront of data storage innovation.
- Benefits: Gain hands-on experience, work with cutting-edge tech, and contribute to impactful research.
- Other info: Dynamic environment with unique cross-disciplinary research opportunities.
- Why this job: Be part of a revolutionary project that redefines how we think about data storage.
- Qualifications: PhD in relevant field, deep learning knowledge, and strong software engineering skills.
The predicted salary is between 60000 - 80000 £ per year.
Machine learning is having a transformative effect on many research areas, fundamentally altering the way many problems are approached, and the scope of what is achievable. Project Silica is developing a revolutionary storage technology by using femtosecond lasers to store data in glass. The project provides an unprecedented opportunity to completely re-think how storage systems are built, and build a storage technology that’s end-to-end optimized solely for the cloud, from the materials level up to the user interface.
Machine learning plays a critical role in the development and existence of the technology, enabling unprecedented information densities to be recorded and successfully read back from glass, facilitating end-to-end optimization of the write and read processes across hardware and software, and more.
The Project Silica team is highly multi-disciplinary, comprising computer scientists, physicists, optical scientists, chemists, electrical and mechanical engineers, and designers. Tackling the hard technical challenges of making glass storage into a real technology presents a myriad of unique opportunities for cross-disciplinary research, including applying machine learning to completely new problem domains.
Contract duration: 2 years.
Qualifications
- Required/Minimum Qualifications:
- Completed (or on-track to complete) a PhD in a relevant discipline.
- Knowledge of deep learning.
- Interest in applied research with real high-world impact.
- Strong software engineering skills and data analysis for rapid and accurate development.
- Creative and collaborative approach to problem solving.
- Preferred/Additional Qualifications:
- Experience optimizing ML [particularly vision] models towards running in production on inference-optimized hardware.
- Publications in top tier conferences.
- Hands-on experience with current deep learning frameworks (e.g., PyTorch, Tensorflow, etc.).
Responsibilities
As a researcher on the project, you will be empowered to collaborate with various members of the team, designing, implementing, and applying machine learning solutions for signal processing to decode data read from glass, with the goal of making Silica into a successful storage technology deployed at scale in the cloud. Problem areas broadly include: computer vision for object detection and recognition, optimization of machine learning models towards running in production, ML-driven discovery and optimization of new physical processes, and more.
ML Researcher: Signal Processing for Glass Storage in Cambridge employer: Microsoft
As an ML Researcher at Project Silica, you will join a pioneering team dedicated to revolutionising data storage technology through innovative machine learning applications. Our collaborative and multi-disciplinary work culture fosters creativity and growth, offering you the chance to engage in impactful research that pushes the boundaries of what's possible in cloud storage. Located in a vibrant tech hub, we provide excellent employee benefits, continuous learning opportunities, and a supportive environment that values your contributions to cutting-edge projects.
StudySmarter Expert Advice🤫
We think this is how you could land ML Researcher: Signal Processing for Glass Storage in Cambridge
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of machine learning and signal processing. Attend meetups, webinars, or conferences related to Project Silica. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving deep learning and data analysis. This is your chance to demonstrate your creative problem-solving abilities and software engineering skills to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of current deep learning frameworks like PyTorch and TensorFlow. Be ready to discuss how you can apply these tools to real-world problems, particularly in the context of glass storage technology.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to make an impact in applied research. Your next big opportunity could be just a click away!
We think you need these skills to ace ML Researcher: Signal Processing for Glass Storage in Cambridge
Some tips for your application 🫡
Show Your Passion for Machine Learning:When writing your application, let us see your enthusiasm for machine learning and its real-world impact. Share specific examples of projects or research that excite you, especially those related to signal processing or storage technologies.
Highlight Your Technical Skills:Make sure to showcase your strong software engineering skills and experience with deep learning frameworks like PyTorch or TensorFlow. We want to know how you've applied these skills in past projects, so don’t hold back on the details!
Emphasise Collaboration:Since our team is multi-disciplinary, it’s important to highlight your collaborative approach. Share experiences where you’ve worked with diverse teams or tackled complex problems together, as this will resonate well with us.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity in Project Silica. Don’t miss out!
How to prepare for a job interview at Microsoft
✨Know Your Stuff
Make sure you brush up on your deep learning knowledge and be ready to discuss how it applies to signal processing. Familiarise yourself with the latest frameworks like PyTorch and TensorFlow, as well as any relevant publications you've contributed to. This will show that you're not just a candidate, but a passionate expert in your field.
✨Show Your Collaborative Spirit
Since the Project Silica team is multi-disciplinary, highlight your experience working with diverse teams. Be prepared to share examples of how you've collaborated with others, tackled complex problems, and contributed to successful projects. This will demonstrate that you can thrive in a collaborative environment.
✨Think Outside the Box
The role requires a creative approach to problem-solving, so come armed with innovative ideas or solutions related to glass storage technology. Think about how machine learning can revolutionise this field and be ready to discuss your thoughts during the interview. This will set you apart as a forward-thinking candidate.
✨Prepare for Technical Questions
Expect technical questions that dive deep into your software engineering skills and data analysis capabilities. Practice explaining your thought process when optimising ML models for production. Being able to articulate your approach clearly will showcase your expertise and readiness for the challenges ahead.
