ScreenPoint is looking for an enthusiastic and skilled software engineer. You’ll be part of a highly motivated and collaborative group of researchers and software engineers with experience in breast imaging, artificial intelligence, algorithm development and clinical research who work closely together in an informal atmosphere.
In this position, you will be responsible for building and maintaining the software and services to effectively bring our AI solutions into clinical practice. This includes understanding complex hospital workflows needs, optimal computation and visualization of our machine learning results, as well as designing, implementing and deploying a variety of services that will be used to effectively test and validate our products.
ScreenPoint seeks talent regardless of gender, age, nationality et cetera: anyone with the relevant skills is invited to apply.
BSc, MSc or higher degree in Computer Science, Software Engineering or equivalent analytical and applied skills.
C++, Linux and scripting.
Excellent verbal and written communications skills.
Experience working in a dynamic environment.
Self-motivated with a high level of energy, enthusiasm and initiative.
Experience working with medical devices, including understanding and previous use of health related standards (i.e. DICOM, HL7).
Experience with git as a version control system.
Experience with Qt.
Experience with network and client security considerations.
Cross platform programming and compiling (Windows and Linux).
Competitive salary applies.
For more information please contact us via e-mail.
To apply for this position send a resume, motivation letter and portfolio (e.g. Github profile) to firstname.lastname@example.org. Applications are processed immediately upon receipt.
ScreenPoint is a leading company that develops and markets breast image analysis and cutting edge machine learning applications and services. Our product Transpara aims at improving breast cancer survival rates by detecting cancers earlier so that treatment can be more effective and less invasive.