Internship – Computational Modelling and Digital Twins of Organoids (f/m/x)
ZEISS · Dresden
Motivation of the work
Turning today’s research into tomorrow’s applications – together.
With a clear focus on user and customer needs, Corporate Research and Technology at ZEISS focuses on developing and advancing future technologies for all business units within the ZEISS Group.
For our team of researchers and engineers at the ZEISS Innovation Hub Dresden, we seek a student to support our concept work on the development of computational models and digital twins of organoids. The project is situated at the interface of artificial intelligence, computational biology, microscopy, and virtual cells.
Your Role
Develop and evaluate computational models for organoid development, morphology, growth, and response to external stimuli
Analyze multimodal biological data, including microscopy images, time-lapse recordings, and potentially molecular or experimental metadata
Design, conduct, and evaluate experiments using simulated and real-world datasets
Investigate existing approaches in scientific literature and adapt them to ZEISS-specific applications
Support the integration of data-driven and mechanistic modelling approaches for improved interpretability and predictive performance
Communicate results clearly and contribute to scientific discussions within an interdisciplinary team
Your Profile
A bachelor’s degree and current enrolment in a master’s program in computer science, bioinformatics, computational biology, physics, mathematics, engineering, or a related discipline
Proficiency in Python for scientific computing, data analysis, statistical modelling, and machine-learning workflows, with the ability to critically evaluate and adapt AI-assisted code.
Ideally, experience in image analysis, computer vision, microscopy, or time-series data analysis
Ideally, knowledge of computational modelling, systems biology, quantitative biology, or organoids
An interest in virtual cells, digital twins, and the simulation of complex biological systems
Excellent organizational, problem-solving, and communication skills
Fluent English; knowledge of German is an advantage
Sounds exciting? Then become part of #teamZEISS and help us shape the future! Please provide your complete application documents (CV, transcript of records, etc.).
Your ZEISS Recruiting Team:
Falk Dymke