Student Project Program - Machine Learning and Signal Processing
The Student Project Program gives you real, hands-on experience in our lab, working with a small, tight-knit team on meaningful, technical problems that actually move the company forward.
Project: Machine learning driven algorithm development for signal processing in applied physics
Close Date: rolling applications
Location: Darlington, NSW with flexible working conditions
Project Overview
We are seeking an enthusiastic intern to join a project that applies machine learning and signal-processing techniques to the analysis of spectral data. The project involves developing algorithms capable of identifying subtle features within noisy or distorted datasets. The goal is to build a robust algorithm that can reliably extract key parameters from real-world measurements.
This project would suit a computer science, electrical engineering or physics student who enjoys working with real data and supporting real world applications.
About Deteqt
Deteqt is an early-stage, venture-backed startup building a diamond-on-chip quantum sensing platform that can detect and measure magnetic fields with unprecedented sensitivity and stability. By leveraging semiconductor manufacturing, our devices will achieve radical reductions in size, weight, power and cost, putting “quantum” into mainstream use.
Our first applications are in GPS-denied navigation, where satellites can be jammed or spoofed, and in critical mineral detection, helping reduce the environmental and economic costs of resource exploration.
Longer term, our sensors have the potential to transform medical diagnostics (MRI, MEG, MCG) and open completely new categories where magnetic-field awareness can be deployed ubiquitously in vehicles, infrastructure, and eventually consumer devices.
Your Key Responsibilities
Work with curated datasets collected under a range of system settings.
Develop, train and evaluate algorithms capable of distinguishing the signal under test from artifacts caused by instrumentation.
Document and communicate results to Deteqt’s technical team to support integration of successful approaches into prototype calibration and system development.
Regular attendance at Deteqt, which is located at the Sydney Knowledge Hub (University of Sydney campus).
Required skills and experience
Strong programming experience and experience with machine learning frameworks in Python.
Ability to design, train, and evaluate machine learning models.
Experience in signal processing (frequency-domain).
Strong analytical thinking and problem-solving abilities.
Ability to work independently with minimal supervision.
Good communication skills for presenting findings.
Curiosity and willingness to learn new tools and concepts.
Desirable skills and experience
Experience in spectroscopy/spectral analysis.
Experience in experimental physics.
What does success in this role look like?
Success in this role is the implementation of the algorithm as a key part of our sensor calibration processes and/or next generation prototype development.
To Apply
Please submit the following to info@deteqt.tech:
Your contact details
Your background: This can be a linkedin, resume, or in paragraph form
What you think you can contribute
Commitment: How long would you like to commit to (and what does that look like on a weekly basis)
Mechanism of engagment: ie does this count for course credit? are you looking for funding through a particular scheme?
Anything else we should know
We are an equal-opportunity employer and welcome applications from individuals of all backgrounds and experiences.
See our progress on linkedin.com/company/Deteqt