Position Description
As a Postdoctoral Researcher at Cinemo, you will help shape and advance cutting-edge research topics at the intersection of Machine Learning, Data Science, GenAI, agentic systems, and modern cloud/backend platforms. You will contribute as an active researcher in the team—quickly assessing emerging directions, translating them into clear research narratives, and turning ideas into demonstrable prototypes and validated results.
A core part of this role is research communication and transfer: identifying suitable funding opportunities, framing research questions to match program goals, and producing high-quality project documentation and proposals in German. You will combine scientific rigor with a pragmatic engineering mindset to bridge research, implementation, and measurable impact.
In this role, you will:
- Explore, assess, and structure new research topics in Machine Learning, Data Science, and Cloud Platforms, translating trends into research roadmaps.
- Design and implement prototypes and proof-of-concepts spanning backend systems, cloud platforms, and AI/ML components.
- Conduct state-of-the-art reviews, benchmarking, and evaluation to position ideas against current research and industry practice.
- Identify relevant public funding opportunities and translate technical concepts into compelling project narratives, objectives, and work plans.
- Write and coordinate high-quality German-language research project proposals and supporting. documentation with internal and external stakeholders
- Collaborate across teams to connect research outcomes with production needs, scalability requirements, and real-world constraints.
What you will need to succeed:
- PhD in Computer Science, Machine Learning/AI, Data Science, Software Engineering, or a closely related field.
- Proven research excellence (e.g., publications, strong methodological foundation, ability to ramp up quickly on new topics).
- Demonstrated experience producing high-quality technical writing (e.g., grant proposals, project descriptions, scientific reports).
- Solid engineering skills across ML and software systems, including Python, modern ML tooling, and backend/cloud architectures.
- Strong ability to connect scientific contributions with practical application, evaluation, and stakeholder needs.
- Very strong written and spoken German and English communication skills (proposal-grade).