Post Doctoral Researcher in Machine Learning (ML) and Solid-State Fermentation
100%, Zurich, fixed-term
We are seeking a highly motivated and interdisciplinary Postdoctoral Researcher to join our team in developing a cutting-edge nutrient prediction platform. This project integrates machine learning with solid-state fermentation (SSF) using filamentous fungi to optimize nutrient profiles in food. The goal is to develop predictive models in fermentation processes to achieve enhanced nutritional outcomes.
Job description
- Design and conduct SSF experiments using selected fungal strains.
- Develop new anayltical approaches to measure and control fermentation conditions and outcomes
- Collect and analyze biochemical data from fermented substrates.
- Develop and train machine learning models to predict nutrient transformations.
- Integrate multi-modal datasets (e.g., chemical, microbial, environmental) into predictive frameworks.
- Collaborate with biotechnologists, data scientists, and food engineers.
- Publish findings in peer-reviewed journals and present at conferences.
Profile
- PhD in Biotechnology, Microbiology, Bioinformatics, Computer Science, or related fields.
- Strong background in machine learning, preferably applied to biological or chemical systems.
- Hands-on experience with solid-state fermentation or fungal biotechnology.
- Proficiency in Python, R, or similar programming languages.
- Excellent communication and teamwork skills.
Workplace
Workplace
We offer
- A dynamic team in an interdisciplinary research environment.
- Access to state-of-the-art lab
- Opportunities for career development and international collaboration.
We value diversity
Curious? So are we.
We look forward to receiving your online application with the following documents:
- PhD certificate
- CV
- Publication list with a clear statement on own contribution
- 2-page proposal/sketch on how to link solid-state fermentation conditions, fungal strains, substrates, and nutritive outcomes. Explain which model you would use and which biochemical assays could be useful.
Please note that we only accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
For further information about the Food Structure Engineering Group, please visit our website. Questions regarding the position should be directed to Patrick Alberto Rühs (patrick.ruehs@hest.ethz.ch) (no applications).
We would like to emphasize that the pre-selection process is conducted by the responsible recruiters, not by artificial intelligence.
About ETH Zürich
Curious? So are we.
We look forward to receiving your online application with the following documents:
- PhD certificate
- CV
- Publication list with a clear statement on own contribution
- 2-page proposal/sketch on how to link solid-state fermentation conditions, fungal strains, substrates, and nutritive outcomes. Explain which model you would use and which biochemical assays could be useful.
Please note that we only accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
For further information about the Food Structure Engineering Group, please visit our website. Questions regarding the position should be directed to Patrick Alberto Rühs (patrick.ruehs@hest.ethz.ch) (no applications).
We would like to emphasize that the pre-selection process is conducted by the responsible recruiters, not by artificial intelligence.