Tech internship: Federated and decentralised machine learning techniques
This internship is perfect for students looking to explore cutting-edge federated learning techniques in the context of indoor localisation, collaborating on a unique decentralised approach.
Apply now for this internship!
About this internship
At Crownstone, we envision smart indoor spaces where devices collaborate securely and efficiently. Our Crownstone devices form intelligent mesh networks, capable of sensing and communicating within their local clusters.Â
In this internship, you’ll explore methods for decentralised, privacy-preserving localisation by enabling Crownstones to collaboratively exchange insights without central data aggregation.
Your task will be to research, design, and implement federated learning techniques enabling Crownstones to jointly improve their localisation accuracy and awareness, while respecting user privacy and data integrity.
What will you do and learn?
This internship is an exciting opportunity to work at the forefront of federated learning and IoT technology. Youâll:
- Research and benchmark federated and decentralised machine learning techniques for indoor localisation.
- Develop algorithms enabling Crownstones to communicate and share localisation insights securely and efficiently.
- Experiment with privacy-preserving AI methods and distributed computing.
- Collaborate closely with our multidisciplinary team of researchers, engineers, and privacy experts.
- Gain practical experience in the dynamic setting of an innovative tech startup.
About you
Ideally, you have the following qualifications:
- Are currently studying computer science, artificial intelligence, distributed systems, data science, or a related field.
- Are in your final year or pursuing a master’s degree.
- Have solid programming skills (Python, Java, or C(++)) and familiarity with AI frameworks.
- Enjoy exploring new concepts in distributed computing and privacy-enhancing technologies.
Itâs a bonus if:
- Have knowledge of federated learning frameworks (TensorFlow Federated, PySyft).
- Are familiar with privacy-preserving techniques (secure aggregation, differential privacy).
- Have prior experience or coursework related to mesh networks or IoT
What can you expect from us
About Almende and Crownstone
This internship is at one of our daughter companies, namely Crownstone.
Crownstone is revolutionizing indoor location tracking, transforming how businesses and technologies interact with physical spaces.Â
Our technology is used for indoor localization, enabling the tracking of various devices like tags, smartphones, and other BLE devices.
Our culture
We are a small-scale and flat organization. The culture is informal, and communication lines are short. We donât like office politics.
At Almende, employees are given the space to work independently. We empower our employees to voice their ideas. If you enjoy taking initiative, have many ideas, and wish to execute them, you’ll feel right at home.
What we offer
- Real hands-on experience: Apply what you’ve learned in your studies to real-life situations
- A peek into the international tech scene
- Build a network with industry pros
- Guidance and mentorship from people who’ve been in your shoes
The application process
Apply
Send us your resume at sander@almende.org
First Meeting
Weâll first check if your profile fits. If yes, youâll meet with the Head of the department.
Second Meeting
Meet one of your future colleagues for an in-depth talk about the subject matter you applied for.
Offer
If there's a mutual connection, we'll make you a great offer. Hopefully, we can welcome you to our team soon!