Opportunities for Master's theses at D-MTEC
Explore opportunities to write your Master's thesis at a research group at D-MTEC or an associated lab. The feed is based on SiROP placements.
Machine Learning for Better Prediction of Market Supplies of Berries and Stone Fruits in Switzerland.
This thesis examines how accurately different forecasting approaches—including machine learning and classical time series models—predict weekly stone fruit and berry market volumes in Switzerland.
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Master Thesis
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Published since: 2026-01-12 , Earliest start: 2026-01-12 , Latest end: 2032-12-31
Organization Chair of Agricultural Economics and Policy D-USYS
Hosts Finger Robert, Dr.
Topics Agricultural, Veterinary and Environmental Sciences
Labour and the transition to sustainable production in Swiss viticulture
This thesis examines the current state of labour in Swiss viticulture, and how this state could influence winemaker’s decision-making ability, using survey data from 489 producers across all major wine regions. Given viticulture’s labour intensity and Swiss viticulture facing a mix of high labour costs and poor mechanisability offers outlook into the economic and environmental sustainability.
Keywords
Labour, Data analysis, Viticulture, Pest Management
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Master Thesis
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Published since: 2026-01-05 , Earliest start: 2026-01-05 , Latest end: 2026-08-03
Applications limited to ETH Zurich
Organization Chair of Agricultural Economics and Policy D-MTEC
Hosts Höper Philipp
Topics Economics
Marginal costs of biodiversity provision in Swiss agriculture
This thesis uses the bio-economic model FarmDyn to quantify the opportunity costs of biodiversity-friendly practices on Swiss dairy and beef farms, based on data from the canton of Grisons. The thesis evaluates the cost-efficiency of various agri-environmental scheme designs to inform biodiversity policy in Swiss mountain agriculture.
Keywords
Biodiversity, agriculture, agri-environmental schemes, opportunity costs, mountain farming
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Published since: 2025-12-12 , Earliest start: 2025-08-01 , Latest end: 2026-08-01
Organization Chair of Agricultural Economics and Policy D-USYS
Hosts Huber Robert , Finger Robert, Dr.
Topics Economics
Master thesis: Crop protection in organic and non-organic pesticide-free arable farming
Pesticide-free (non-organic) crop production is currently gaining ground in European agriculture as a new alternative pathway between conventional and organic farming. To successfully produce crops without using pesticides, farmers must adopt sustainable crop protection measures, e.g., following the principles of integrated crop protection (IPM) or agroecological crop protection (ACP). Even though both production systems, i.e., pesticide-free non-organic and organic, work without pesticides, the alternative crop protection measures used may differ between organic and non-organic farms. To date, little is known about potential differences between farming systems without pesticides regarding the adoption of alternative crop protection strategies.
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crop protection, pesticide-free, organic, integrated pest management (IPM), wheat, maize, Switzerland
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Master Thesis
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Published since: 2025-12-11 , Earliest start: 2025-02-02 , Latest end: 2026-01-22
Organization Chair of Agricultural Economics and Policy D-MTEC
Hosts Akter Sharmin
Topics Agricultural, Veterinary and Environmental Sciences
Master Thesis Economics of spatial and temporal information for improving nitrogen efficiency in agriculture.
Background Switzerland has ambitious goals to reduce nitrogen surpluses in agriculture. An important mechanism in this context is to improve nitrogen efficiency. In this context, new technologies such as precision farming, and remote sensing and new sensors can provide better information on nutrient availability in the field. In the past, these efforts were mainly focused on improving spatial application patterns. This thesis aims to also include the temporal application pattern, i.e. when to apply fertilizer. Such spatial and temporal information can help farmers avoid nitrogen losses by applying the right amount of fertilizer at the right time and place to meet crop needs. Soil health sensors (such as those developed by Digit Soil) can provide additional information about the timing of fertilizer application. Combining spatial and temporal information about fertilizer application could improve nitrogen efficiency in crop production and contribute to a more sustainable agricultural sector. Research questions ● What are the economic costs and benefits of knowing when to fertilize? ● How big is the potential to reduce fertilizing by using temporal information? ● What is the potential of spatial and temporal information for achieving nitrogen efficiency goals in Swiss agriculture?
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-12-09 , Earliest start: 2025-09-01 , Latest end: 2026-12-31
Organization Chair of Agricultural Economics and Policy D-MTEC
Hosts Finger Robert, Dr.
Topics Agricultural, Veterinary and Environmental Sciences , Economics
What factors determine whether farmers exceed the minimum uptake requirements of voluntary agri-environmental schemes – the case of the reduced tillage scheme in Switzerland.
The case study would be based on the reduced tillage scheme, where to qualify, farmers must perform ploughless cultivation on at least 60% of their arable land using either mulch, strip tillage, direct drilling, or a combination of these methods. However, many farmers exceed the bare minimum levels needed to qualify and, as such, “over-perform” relative to the basic incentive. The analysis would utilise farmer characteristics, farm usage of complementary practices, and structural data to understand the determinants of “over-performance” adoption among farmers. This is an important policy question, as it may help determine which factors can be harnessed to improve the uptake and impact of soil conservation schemes. Additionally, this analysis could shed some light on aspects such as the additionality of current soil conservation schemes relative to the uptake behaviour of farmers, irrespective of the current scheme requirements.
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You will use the following Data: InBestSoil Data + Spatial Data: Data covering soil management practices and farm characteristics on Swiss arable farms | Scientific Data (Document attached)
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Master Thesis
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Published since: 2025-12-09 , Earliest start: 2025-12-09 , Latest end: 2026-12-09
Organization Chair of Agricultural Economics and Policy D-USYS
Hosts Finger Robert, Dr.
Topics Agricultural, Veterinary and Environmental Sciences
Falling Through the Cracks: Understanding Non-Participation in Direct Payment Schemes among Swiss Grape Growers
This thesis examines factors behind non-participation in direct payment schemes by grape growers in Swiss viticulture using survey data from 489 producers across all major wine regions. Given viticulture’s high pesticide use and economic importance, the thesis offers policy-relevant insights into the effectiveness of agri-environmental programs.
Keywords
Agricultural Policy, Data analysis, Viticulture, Pest Management
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Master Thesis
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Published since: 2025-12-08 , Earliest start: 2025-12-08 , Latest end: 2026-07-06
Applications limited to ETH Zurich
Organization Chair of Agricultural Economics and Policy D-MTEC
Hosts Zachmann Lucca
Topics Economics
How Good Is My Heat Pump? Developing Context-Driven Performance Benchmarks
Heat pumps are becoming one of the most important technologies for decarbonizing residential heating across Europe. Their efficiency is typically expressed through the coefficient of performance (COP), which describes how much heat a heat pump produces per unit of electrical energy consumed. COP values are used by installers, manufacturers, policymakers, and homeowners to judge how well a heat pump is performing. However, interpreting COP values is far from straightforward. A COP of 3.0 might be excellent on a very cold winter day with high supply temperatures, but the same COP could indicate poor performance under milder conditions. Today, COP evaluations often rely on mean values reported in studies or monitoring campaigns—but these averages do not capture the large variability in real-world operation. As a result, heat pumps are frequently judged unfairly or incorrectly, leading to confusion, misdiagnosis of system issues, and suboptimal design or control decisions. To make performance evaluation more reliable, we need context-aware benchmarks: reference COP values tailored to specific operating conditions such as outdoor temperature, supply temperature, heating system type, building characteristics, and user behavior. Such benchmarks would enable installers, service teams, and homeowners to quickly determine whether a heat pump is performing as expected in its situation, instead of comparing it to generic averages.
Keywords
Heat pump performance, context-aware evaluation, applied machine learning, AI, sustainable heating
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-11-27 , Earliest start: 2025-12-01
Organization Bosch IoT Lab
Hosts Potthoff Ugne
Topics Information, Computing and Communication Sciences , Engineering and Technology , Architecture, Urban Environment and Building , Physics
Scaling Expert Assessments Through AI and LLM-Based Reasoning: A Real-World Heat Pump Performance Assessment
system is configured correctly and running efficiently. This manual evaluation requires specialized knowledge, does not scale well, and can delay the detection of installation issues. With the rapid advancement of large language models and autonomous agent systems, there is a promising opportunity to automate parts of this expert reasoning process. In this thesis, you will investigate whether LLM-based agents can understand and interpret heat pump performance data in a way that mirrors human expert evaluations. You will study how experts identify typical installation problems, derive the key features and patterns from time-series data that are necessary for assessment, and design an AI workflow capable of generating explanations and recommendations. The work includes preparing data, experimenting with different model architectures and representations, and building a prototype system that evaluates performance and flags potential issues. The goal is to deliver a validated proof-of-concept that demonstrates how AI can support or partially automate expert feedback, ultimately enabling scalable, consistent, and timely assessments for large fleets of connected heat pumps. This project combines applied machine learning, energy systems knowledge, and agentic AI design, in collaboration with the ETH Agentic Systems Lab and the Bosch Lab.
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LLMs, Agentic AI, Time-Series, Applied Machine Learning, Energy Tech Innovation, Automated Diagnostics, Heat Pump
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Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-11-18 , Earliest start: 2025-12-01
Organization Bosch IoT Lab
Hosts Potthoff Ugne
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Earth Sciences
AI for Supporting a Scalable Transition to Sustainable Heating in Residential Buildings
Heating systems in European homes were rarely designed with modern heat pumps in mind. When upgrading such buildings, one of the most important questions is whether the existing radiators can deliver enough heat to keep rooms warm under winter design conditions. Knowing the heating power of each radiator is essential for correctly sizing a heat pump, ensuring comfort, and avoiding costly mistakes. Yet most homeowners and many installers do not know which radiators are installed, how large they are, or what their thermal output is. Traditional assessments require manual measurements, catalog lookup, or accessing technical data that may be unavailable or difficult to interpret. With advances in artificial intelligence - especially computer vision and reasoning models - we now have the opportunity to automate this entire process. Instead of manual work, a homeowner or installer could simply take a few photos of each radiator. An AI system could then recognize the radiator type, estimate its dimensions, and calculate its expected heating power at typical operating conditions. Such a tool would significantly simplify and speed up heat load calculations, which form the foundation for designing efficient, reliable heat pump systems in existing homes. This research aims to explore how AI can bridge this gap by interpreting real-world images and transforming them into actionable engineering information.
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Computer Vision, AI, Automated Assessment, Heat Pump, Reliability Analysis
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Collaboration , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-11-18 , Earliest start: 2025-12-01
Organization Bosch IoT Lab
Hosts Potthoff Ugne
Topics Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Earth Sciences , Physics
Analysing the potential of multi-yield index insurance to cope with heat and/or drought risks
The agricultural sector is exposed to yield risks, such as weather anomalies (e.g. Beillouin et al., 2020; Schmitt et al., 2022). Farmers can implement on-farm and off-farm risk management strategies to mitigate these risks (Bardaji, 2016; OECD, 2021). On-farm strategies include crop diversification, while off-farm strategies include insurance. Farmers often combine these strategies. However, crop insurance across Europe currently does not take crop diversification opportunities into account in the insurance design. This master's thesis will evaluate the potential of multi-yield index insurance as an option to help farmers cope with weather risks such as heat and/or drought.
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Risk Management; Index Insurance; Diversification
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Master Thesis
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Published since: 2025-10-16 , Earliest start: 2025-11-01 , Latest end: 2026-06-30
Organization Chair of Agricultural Economics and Policy D-MTEC
Hosts Schmitt Jonas
Topics Agricultural, Veterinary and Environmental Sciences