Marco Bühler
Marco Bühler
Student / Programme Doctorate at D-CHAB
ETH Zürich
Additional information
Research area
Marco Bühler joined the Sustainable Process Engineering Lab as a PhD student in 2024, following a Master’s degree in Chemical and Bioengineering from ETH Zürich, where he wrote a thesis on designing synthetic peptides to modulate biomolecular condensate behavior using MILP and Machine Learning. He is currently researching symbolic regression and interpretable machine learning techniques under the supervision of Prof. Gonzalo Guillén Gosálbez.
Alongside research, Marco works as a teaching assistant for Chemometrics and Machine Learning for Chemical Engineers. His work contributes to broader questions in machine learning in engineering subjects, with a focus on equation discovery in dyamic systems.
Work Experience
Since 10/2024PhD Student in Chemical Engineering, ETH Zürich
10/2023-02/2024 Research Assistant, Functional Materials Lab, ETH Zürich
03/2023-05/2023 Downstream Process Modelling Engineer, DataHow AG
02/2023-07/2023 Teaching Assistant, Chemometrics and Machine Learning for Chemical Engineers, ETH Zürich
09/2022-02/2023 Internship, Upstream Process Modelling Engineer, DataHow AG
04/2022-07/2022 Research Assistant, Functional Materials Lab, ETH Zürich
Education
2023-2024 Master of Science in Chemical and Bioengineering, ETH Zürich
02/2024-08/2024 Master Thesis, ETH Zürich
2019-2021 Bachelor of Science in Chemical Engineering, ETH Zürich