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Project Overview | Project Code: NAT 02 |
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| Project name: | Machine learning in electrochemistry |
| TUM Department: | NAT - Chemistry |
| TUM Chair / Institute: | Digital Catalysis |
| Research area: | Electrochemistry, Batteries, Machine Learning |
| Student background: | Chemical Engineering |
| Further disciplines: | |
Planned project location: | Offices and labs of the Professorship for Digital Catalysis in Garching - Forschungszentrum Garching Chemistry Department and Catalysis Research Center |
Project Supervisor - Contact Details | |
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| Title: | Prof. Dr.-Ing. |
| Given name: | Helge |
| Family name: | Stein |
| E-mail: | helge.stein@tum.de |
| Phone: | 015141223478 |
Additional Project Supervisor - Contact Details | |
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| Title: | M.Sc. |
| Given name: | Leah |
| Family name: | Nuss |
| E-mail: | leah.nuss@tum.de |
| Phone: |
Additional Project Supervisor - Contact Details | |
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| Title: | |
| Given name: | Fuzhan |
| Family name: | Rahmanian |
| E-mail: | fuzhan.rahmanian@tum.de |
| Phone: |
Project Description | |
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| Project description: | We will explore lab automation and data analysis for electrochemical experiments. The Project will most likely revolve around synthesis and characterization of nanoparticles or microparticles for catalysis and or batteries. We have a series of robotic setups that allow us to generate pertinent data for all kinds of applications. For this project call we will offer a projects related to: |
| Working hours per week planned: | 40 |
Prerequisites | |
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Required study level minimum (at time of TUM PREP project start): | 2 years of bachelor studies completed |
| Subject related: | Proficiency in either julia or python |
| Other: |