Intern Advanced Research - MV Anomaly Detection

OUR STORY

At ST, we believe in the power of technology to drive innovation and make a positive impact on people, business, and society. We are a global semiconductor company, and our advanced technology & chips forms the hidden part of the world we live in today. 

When you join ST, you will be part of a global business of more than 115+ nationalities and present in 40 countries, 50,000+, diverse and dedicated creators & makers of technology around the world!

Developing technologies takes more than talent: it takes amazing people who understands collaboration and respect. People with passion and desire to disrupt the status quo, push boundaries and drive innovation – whilst unlocking your own potential. 

Working at ST means innovating for a future that we want to make smarter, greener, in a responsible and sustainable way. Our technology starts with you. Join us and start the future!

YOUR ROLE 

Are you enthusiastic about the intersection of sensors data and machine learning? Do you aspire to contribute to innovative research that improve the world of anomaly detection? We are offering an exciting thesis opportunity focused on benchmarking state-of-the-art (SOTA) algorithms on our multivariate anomaly detection dataset: IMAD-DS.

Key Responsibilities:

• Development of Machine Learning Algorithms: Evaluate and benchmark SOTA anomaly detection algorithms on the multivariate dataset, analyzing their performance and robustness. You will eventually propose your novel algorithm!


• Optimization of data pipelines: Improve our data pipelines to manage and preprocess the datasets, ensuring high-quality input for benchmarking: your aim is to make them more robust and efficient!


• Implementation on Microcontroller-Based Systems: Bring your solutions to life by implementing them on microcontroller-based systems, ensuring they are practical and efficient.


• Academic Contributions: Occasionally contribute to the academic community by writing and submitting papers to conferences and journals, sharing your research and insights.

Join us in this thrilling journey to transform how multivariate data is interpreted and analyzed. This thesis opportunity is perfect for those who are passionate about research, innovation, and making a tangible impact in the field of anomaly detection. Apply now and be part of a pioneering project that combines creativity with cutting-edge technology.

YOUR SKILLS & EXPERIENCES

• Currently enrolled in engineering Master’s Degree.


• Understanding of machine learning fundamentals, including deep learning and neural networks.


• Proficiency in Python, C, C++


• Proficiency in AI/ML frameworks tools Tensorflow, PyTorch.

We encourage candidates who may not meet every single requirement to apply, as we appreciate diverse perspectives and provide opportunities for growth and learning. Diversity, Equity and Inclusion (DEI) is part of our company culture. Our DEI vision is, “At ST, you can be the true version of yourself”, we value all employee contributions and have zero tolerance for any kind of discrimination. 

Joining us is also about a greater work-life balance and workplace with equal opportunities. Dedicated Employee Resource Groups for women and LGBTQIA+, hybrid work arrangements are amongst the many DEI & Sustainability initiatives that make us a great place to evolve your career.

To discover more, visit st.com/careers