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As a deep learning developer at MRIguidance, a UMC Utrecht spin-off company, you will apply the newest deep learning methods on unique 3D medical image data sets of real patients to develop algorithms that characterize human anatomy and aid doctors and patients in hospitals worldwide.
What you tell at birthdays about your job
“My software prevents cancer in patients that need to undergo a bone scan. It creates images that help doctors to better diagnose and cure their patients.”What you actually will be doing."
What you actually will be doing
You will be a key contributor to the core development of our MRI data analysis pipeline for the visualization and characterization of different human tissues. You are an innovative thinker who will be developing deep learning methods and algorithms, exploiting our unique patient data sets. You like to learn new things. With the team, you will integrate these solutions into our products. Your results will boost our technology and help us to achieve high quality, clinical grade products. Your solutions will soon be used in clinical patient examinations. You will use agile and scrum methods and work in vibrant entrepreneurial team of image scientists and developers.
Your responsibilities:
Minimum qualifications:
Preferred qualifications:
This is what we offer you:
During their research MRI physicist Peter Seevinck and medical image scientist Marijn van Stralen identified great unused potential for MRI-based medical imaging technologies. Together with Roel Raatgever, former director of Europe’s no.6 academic business incubator UtrechtInc, they have founded UMC Utrecht spin-off company MRIguidance. The team of MRIguidance actively collaborates with hospitals in the Netherlands and abroad to acquire unique patient data sets and clinically validate the results of the deep learning developments. MRIguidance’s products will improve diagnosis and treatment decisions. Through collaboration with 3D medical printing partners (e.g. 3DMedical) , their imaging solutions will serve as input for 3D printed personalized implants and medical devices.
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