deepeye Medical
Internship/Master Thesis Data Engineering/Science for Medical Imaging (w/m/d)
Internship
Your responsibilities
- Your main task is to prepare data for analytical or operational uses, i.e. by integration, consolidation, cleansing and structuring of data
- You are responsible for building and optimizing data pipelines to bring together information from different source systems, i.e. imaging and clinical data
- You are great in your job when your fellow data scientist always have easy access to tools and data needed to carry out their deep learning experiments
What we are looking for
Your must-haves
- Experience in data engineering related to computer vision and imaging analysis (2D/3D image processing, segmentation, image normalization, ideally medical imaging)
- Applied knowledge of deep and machine learning (ML) techniques
- Experience in programming in Python, in developing software in AI and data-centric domains
- Experience in working with relational databases (e.g. PostgreSQL), and modern, scalable storage technologies (e.g. Azure FileShare)
Your nice-to-haves
- Studies in data science/engineering, bioengineering, computer science, medical physics or similar
- Experience using Docker, setting up containerized solutions, cloud deployment and hosting
- Working-level English (C1 or higher)
What we offer
- Payment, startup culture & a great, international team
- High personal responsibility for your project & fast personal growth
- Flexible working hours, remote work & central office in Munich’s best startup hub
- Direct impact on improving quality of life for our end users (patients)
How to apply
Reach out to us with information about your availability and a link to your conclusive profile (GitHub, LinkedIn, CV). We do not require a motivation letter, but if you like please share with us in 2-3 sentences why you want to help us in preventing blindness with AI.
deepeye Medical
Our mission is to prevent vision loss and ultimately blindness by developing AI software that assists eye doctors in therapy planning for their patients. We use computer vision deep learning models(AI) trained on thousands of cases and millions of images to identify and predict disease progression. The decision support algorithm targets popular eye diseases like Age-related Macular Degeneration (AMD, 7.5mio affected in Germany alone).