Machine Learning Engineer - Medical Imaging
Our client are a pioneering medical devices company who develop and commercialise radio-wave radar breast imaging technology. With the current screening system, based on X-rays, detecting only 28% of all breast cancers each year, despite a $1bn global mammography market, they believe that the solution to tackling this disease is frequent screening from an early age. X-rays are not able to deliver this. Their solution is quick, comfortable and non-ionising, supporting a paradigm-shifting approach to beating breast cancer.
The Machine Learning Engineer will be responsible for detailed analysis of a medical imaging system that transmits RF signals into the patient. With many antennas, each antenna transmits in turn with the other receiving signals. Disregarding reciprocal channels, there are roughly 2500 frequency responses per scan and we believe that from within this data we can discern a value for density.
The data requires detailed analysis and an assessment of the most suitable machine learning toolsets to solve the problem and provide a reliable and stable solution.
The Machine Learning Engineer will contribute to development and industrial research in support of the Company’s active R&D work streams. Responsibilities will include for the evaluation, design, and improvement of our radio-frequency imaging system and techniques for medical applications. Developing algorithm and implementing imaging and analytical aspects of the commercial software.
Develop and implement novel radio-frequency imaging techniques for medical applications;
- Assessing technologies to improve/ extend the Company’s radio-frequency imaging capabilities;
- Making contributions to R&D resulting in novel functionality and new product offerings;
- Documentation in the form of technical papers, and presentations; and
- Contribute in patents application.
Essential Knowledge, Skills and Abilities:Experience with pattern recognition techniques, e.g. feature extraction and classification.
- Experience with Big Data machine learning toolkits and/or cloud-based solutions.
- Hands-on experience of experimental work and management of huge volumes of data, its collection and analysis.
- MATLAB (or close equivalent) prototyping skills.
Desirable:Experience working in a regulated commercial environment (medical, aviation, automotive) including traceability requirements and risk management.
- Good solid background in signal processing.
- Experience in medical imaging or biomedical signal statistical analysis.
- Knowledge of medical imaging (e.g., Ultrasound, CT, and/or MRI) theory, reconstruction and applications.
- Experience in software and hardware system development.
- Experience in radar imaging techniques including synthetic aperture radar (SAR) and the ability to develop new algorithms and techniques related to radar imaging, such as algorithms involving image focusing & reconstruction, beam-forming, radar cross-section analysis, automatic target recognition, array & antenna simulation, wave propagation inverse scattering etc.
- C,C++, C#, Python, Object Oriented Programming, familiar with Visual Studio. Familiar with code version control.