The maritime shipping sector is one of the most challenging industries to decarbonize, due to its reliance on high energy-density fuels, long-haul global operations, and limited technological alternatives. While electrification may offer solutions for short-distance or smaller vessels, heavy-duty shipping requires alternative fuels that can deliver comparable performance and global scalability.

Green methanol and ammonia are among the most promising options for this sector, offering viable pathways to decarbonize without sacrificing range or fueling speed. However, key questions remain regarding the cost-effectiveness, infrastructure requirements, and geographic deployment strategies for these fuels. 

In this context, we offer a master’s thesis project aimed at identifying realistic, regionally adapted deployment strategies for renewable fuel infrastructure that can support the decarbonization of the heavy-duty maritime sector. A Python-based geospatial model will be developed to assess the cost, location, and scalability of port-based green fuel hubs.

Key research Tasks

• Analyze existing decarbonization plans of global shipping organizations or corresponding grey literature and industry reports
• Conduct a techno-economic assessment of shipping decarbonization technologies (e.g., green ammonia, methanol, hydrogen, batteries), focusing on fuel properties, infrastructure requirements, and sector-specific limitations
• Model global heavy-duty maritime freight flows using spatial data on ports, trade volumes, and shipping routes to identify high-impact fuel demand corridors
• Develop a Python-based geospatial cost model for introducing port-based green fuel hubs (e.g., bunkering infrastructure, storage, on-site production)
• Identify strategic synergies by analyzing how specific port locations can benefit from co-deployment with local industrial capabilities (e.g., chemical industry, fertilizer production, logistics hubs), and how these synergies can inform cost-effective and scalable rollout strategies

Requirements

• Strong interest in renewable energy, green hydrogen and data analysis
• Background in engineering, environmental sciences, energy systems, economics, or other relevant disciplines
• Experience with Python and a willingness to further develop technical skills
• Familiarity with geospatial analysis tools such as QGIS, ArcGIS, or Python-based GIS libraries is advantageous
• Fluency in English is essential

Setup

• You will be supervised by Prof. Florian Egli and Leander Müller
• Access to an interdisciplinary team with extensive expertise in climate and energy policy and state-of-the-art research methods
• Involvement in research with direct links to policymakers and policy impact
• An exciting community at the School of Social Sciences and Technology
• Close collaboration with the TUM Think Tank
• Access to a lovely office space right in the heart of Munich

How to apply

To apply please send your CV, Transcript of Records and a short motivational statement (max 300 words, all documents in PDF format) to and send it to: leander2.mueller(at)tum.de. 

We evaluate applications on a rolling basis starting on 1 October 2025 and until the position is filled. The start date is as soon as possible.

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To apply, please send an email with subject: “Application to FECS class 2025” to clemens.lehofer@tum.de. The email should contain the title of your PhD or main research project and a 200-word motivation. Deadline for applications is 9 January 2025.