Research & Development Engineer

  • Job Reference: GS-RE-B-0920-2
  • Date Posted: 12 October 2020
  • Recruiter: Software Personnel International
  • Location: Remote
  • Salary: £400 to £500 Per Day
  • Sector: I.T. & Communications, Software Engineering, Medical Devices, Data & Analytics
  • Job Type: Contract - Outside IR35
  • Duration: 3 - 6 months
  • Contact: Gary Smith
  • Email: gary@softwarepersonnel.co.uk
  • Telephone: 01273 891 239

Job Description

Job Title: Research & Development Engineer

Location:  Remote, Home Based

Contract: 3 – 6 Months

Rate: £400.00 - £500.00 per day

 The Company:

Our client are a pioneering medical devices company who develop and commercialise radio-wave radar imaging technology.

The Task:

The Machine Learning Engineer will be responsible for detailed analysis of a medical imaging system.

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.

 Key Skills: Machine Learning Engineer - Remote

  •  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.
  • C, C++, C#, Python, Object Oriented Programming, familiar with Visual Studio. Familiar with code version control.

 Desirable Experience: Machine Learning Engineer - Remote

 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.

Detailed Description:

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.

 This will include slicing and dicing the data all ways, trying different ML tools / techniques in different combinations. Identifying bias in the data and seeking to normalise the bias out. Preparing solutions and testing them against the data we have. Preparing and conditioning the data before you process it through the toolsets. Then it’s reviewing the results to see what you’ve got and make sense of them.

 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.

 Responsibilities:

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.