At a Glance
- Tasks: Collaborate on groundbreaking machine learning solutions for innovative glass storage technology.
- Company: Join a multi-disciplinary team at the forefront of tech innovation.
- Benefits: Gain hands-on experience and contribute to impactful research with real-world applications.
- Other info: Two-year contract with unique opportunities for cross-disciplinary research.
- Why this job: Be part of a revolutionary project that redefines data storage and cloud technology.
- Qualifications: PhD in relevant field, deep learning knowledge, and strong software engineering skills.
The predicted salary is between 30000 - 40000 £ 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.
Cambridge Residency Programme : Machine Learning for Signal Processing employer: Microsoft
As an employer, we offer a unique opportunity to work at the forefront of technology with Project Silica, where machine learning meets innovative storage solutions. Our collaborative and multi-disciplinary work culture fosters creativity and growth, providing employees with the chance to engage in impactful research while developing their skills alongside experts from various fields. Located in Cambridge, a hub for cutting-edge research and development, we provide an environment that encourages professional advancement and meaningful contributions to transformative projects.
StudySmarter Expert Advice🤫
We think this is how you could land Cambridge Residency Programme : Machine Learning for Signal Processing
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend relevant events, and connect with professionals on LinkedIn. We can’t stress enough how important it is to make those connections; you never know who might help you land that dream job!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to machine learning and signal processing. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common interview questions related to machine learning and be ready to discuss your past projects. We recommend doing mock interviews with friends or mentors to build confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. So, get your application in and let’s make some magic happen together!
We think you need these skills to ace Cambridge Residency Programme : Machine Learning for Signal Processing
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 have inspired you, especially those related to signal processing or storage technologies.
Highlight Relevant Experience:Make sure to detail your experience with deep learning frameworks like PyTorch or TensorFlow. We want to know how you've applied these skills in practical settings, so don’t hold back on showcasing your hands-on experience!
Be Creative and Collaborative:Since our team is multi-disciplinary, emphasise your collaborative spirit and creative problem-solving skills. Share instances where you’ve worked with diverse teams or tackled complex challenges in innovative ways.
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 the Cambridge Residency Programme!
How to prepare for a job interview at Microsoft
✨Know Your Machine Learning Stuff
Make sure you brush up on your deep learning knowledge and be ready to discuss how it applies to signal processing. Be prepared to share examples of your past work, especially any projects that involved optimising ML models or using frameworks like PyTorch or TensorFlow.
✨Show Off Your Collaborative Spirit
Since the Project Silica team is multi-disciplinary, highlight your experience working with diverse teams. Share specific instances where you collaborated with others to solve complex problems, and emphasise your creative approach to tackling challenges.
✨Prepare for Technical Questions
Expect some tough technical questions related to machine learning and software engineering. Brush up on key concepts and be ready to explain your thought process when solving problems. Practising coding challenges can also help you feel more confident.
✨Express Your Passion for Real-World Impact
This role is all about applying research to make a real difference. Be sure to convey your enthusiasm for applied research and how you see your work contributing to innovative storage technologies. Share your vision for the future of data storage and how machine learning plays a role in it.
