Introduction
At Atomionics, we build quantum gravimeters that are set to revolutionize the resource exploration industry. We are looking for a motivated intern with experience in time-series machine learning to contribute to the development of our high-performance sensors.
Responsibilities
- Design and implement a machine learning model to map time-series data from support sensors to our quantum gravimeter data.
- Evaluate model performance on both synthetic and experimental datasets.
- Work closely with our multidisciplinary team to validate results and address challenges such as limited data coverage or overfitting.
- Visualise the performance of the model as well as intermediate outputs.
Qualifications
- Education background physics, engineering, or data science is highly desirable.
- Hands on experience with neural networks applicable to time-series data
- Strong Python programming skills: NumPy, SciPy, pandas, visualization packages
- Proficient with ML libraries such as PyTorch/TensorFlow/Keras, etc.
- Familiar with signal processing basics: Fourier transform, windowing, filtering
- Analytical mindset
About the Company
Atomionics Pte. Ltd.
Atomionics is a Singapore-based startup building quantum sensors for subsurface exploration and universal navigation. Our sensors generate 3D models of the Earth’s subsurface to pinpoint critical resources, enable GPS-free positioning, and detect earthquakes and volcanic activity.
We specialize in cold atom interferometry—cooling atoms to near absolute zero with lasers to measure tiny gravitational changes. We’re a hands-on, high-energy team operating at the intersection of quantum physics, hardware, and AI. Engineers here work across mechanical, electronic, and software systems—treating every challenge as a workout for the mind.
Backed by Wavemaker, SGInnovate, Cap Vista, 500 Startups, Paspalis, and prominent angel investors, we’re turning deep tech into real-world impact.