This is a specialised role calling for a mathematically-minded PhD-qualified software engineer with strong algorithmic skills including image processing to extract 3D geometry.Joining this research effort, you would develop algorithms and software to extract and track the evolution of 3D features from colossal quantities of image data. To succeed, you will need to be able to write robust and well-designed Python code, have a very good understanding of algorithmic approaches to extract and characterise 3D objects, cope well with extremely large data sets (TB), and have an inventive approach to problem solving.This work will feed into broader research in the healthcare sector, and will therefore ultimately have a positive impact in society. The work environment is forward-looking and inclusive, and places an emphasis on employee development. Internal and external training is available for areas where skills need further enhancement.You will need:An outstanding academic background with a minimum 2.1 degree in Computer Science or a related STEM discipline and a relevant PhDExcellent mathematical skills and knowledge of feature extraction techniques including CNNsDemonstrably strong software engineering skills and ability to write well-designed code using PythonThis role is based in modern well-equipped offices and labs in Cambridge. Initially, a 3-year fixed term contract, the role has potential to transition to a permanent position in the longer term. Flexible hours and hybrid working are available.Keywords: Image processing, 3D, CNN, Python, Neural Network, Feature Extraction, Healthcare, Research, CambridgeInterested? Send your CV to ECM Selection. We do read every CV and try to respond to everyone. Or recommend a friend for £250, details at https://ecmselection.co.uk/tell-a-friend.Please note: even if you don't have exactly the background indicated, do contact us now if this type of job is of interest - we may well have similar opportunities that you would be suited to. And of course, we always get your permission before submitting your CV to a company. #J-18808-Ljbffr