Machine Learning Engineer - Medical Imaging
An opportunity to join a visionary medical imaging company designing and developing leading edge cancer treatment technology.
The Machine Learning Engineer will be 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 machine learning toolkits and/or cloud-based solutions.
- Learning algorithms
- Supervised Learning: target / outcome variable (or dependent variable)
- Regression, Decision Tree, Random Forest, KNN, Logistic Regression etc.
- Hands-on experience of experimental work and management of huge volumes of data, its collection and analysis.
- MATLAB (or close equivalent) prototyping skills.
- 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# Object Oriented Programming, familiar with Visual Studio. Familiar with code version control.