Job Description

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

What can we offer you

A chance to learn about the intricacies of deep tech research, product development, and strategy in a high-growth startup Work on the cutting edge of quantum technology A book allowance to help you grow and collectively build the Atomionics library * Board games and curry night