(Senior) Software and Data Engineer (Digital Health Research) (f/m/d)

at  D4L data4life gGmbH

HI THERE!

Are you passionate about science and research but look for more practical applications?
Do you know how to turn data into knowledge?
Are you eager to learn new things and implement your own ideas while working with an international and passionate team of professionals?
Then join us and contribute to digital research solutions that have a meaningful impact on healthcare and science in order to support researchers in their day-to-day work!

GOOD TO KNOW

• We especially welcome applicants from the LGBTQI+ community, people with a migration background, people of color, and individuals with disabilities or chronic illnesses to the team.
• If you need support or special assistance during the application or interview process due to a disability, please feel free to let us know and we are happy to accommodate you as much as possible.
• Please enclose your complete documents (CV, letter of motivation, references, salary expectations and earliest possible starting date) with your application.

ABOUT US

Data4Life is a nonprofit organization with the vision of making the world a healthier place. With an international team, we work together on the mission to digitize health research. By linking technology and research, we make health data available to research in a comprehensive, digital and secure way. Our interdisciplinary team in Potsdam, Berlin and Singapore brings together experts from fields such as product development, digital engineering, data security and science. Data4Life was founded in 2017 and is funded by the Hasso Plattner Foundation.

• You will work closely with our partners at the Hasso Plattner Institute in Potsdam, the Icahn School of Medicine at Mount Sinai in New York and our development team in Singapore.
• You will design and implement a framework for secure annotation of radiology images by writing maintainable and well-tested code following best practices.
• You will help to design machine learning pipelines that support our partners in efficiently and securely training and testing machine learning models on structured and unstructured data.
• You will be responsible for the transformation steps of ETL pipelines for data integration from different sources into our common data model.
• You will grow your understanding of the Observational Medical Outcomes Partnership (OMOP) Common Data Model, a globally used standard for representing observational health data.
• You will collaborate with our partner research institutions in summarizing scientific and technological progress in research reports and publish and present them at international conferences.