ScreenPoint Medical is looking for a highly motivated and ambitious research scientist. Your mission will be to apply the latest developments on machine/deep learning to improve our algorithms for automated detection of breast cancer in mammography images and digital breast tomosynthesis volumes. You’ll be part of a motivated and collaborative international team of researchers and software engineers with experience in breast imaging, machine learning, algorithm development and clinical research who work closely together in an informal atmosphere. You will have access to one of the largest annotated databases of mammograms existing today, a professional software infrastructure, and a high performance computing platform with GPUs.
Master’s or PhD’s degree in Computer Science, Mathematics, Physics or related field.
Programming experience with a desire to learn new programming languages.
Fluent in English.
Solid experience in machine learning and willing to extend your knowledge in the field of deep learning and big data.
Enthusiastic about using state-of-the-art technology to solve real clinical problems.
Familiar with Linux environment.
Excellent skills in C++ and Python programming languages.
Practical experience with Deep Learning.
Good understanding of theoretical concepts in machine learning.
Experience in image processing and medical imaging field.
Competitive salary applies.
For more information please contact us via e-mail.
To apply for this position send a resume and motivation letter to firstname.lastname@example.org. Applications are processed immediately upon receipt.
ScreenPoint is a leading company that develops and markets image analysis and machine learning applications and services to improve early detection of breast cancer. The company is a spin-off of the Radboud University in Nijmegen. Our product Transpara uses the latest developments in machine learning such as Deep Learning and is trained with very large well curated databases of screening mammograms. Research and development at ScreenPoint is aimed at improving performance to the level of expert radiologists and beyond.
The company is located in Nijmegen at Toernooiveld, only a few minutes by bus or train from Nijmegen Centraal Station.