Automatic Segmentation of Nanoparticles in Scanning Transmission Electron Microscopy Images by Deep Learning
The Electron Microscopy Center at Empa Dübendorf is offering an exciting project that will provide the candidate with hands-on experience synthesizing catalyst model systems, operating an aberration-corrected transmission electron microscope, generating synthetic data, and training supervised machine learning models.
Identification of optimal technological assets for prosumer communities in the Swiss scenario
Prosumer communities leverage and share locally generated energy. In response to the Swiss Energy Strategy 2050 and potential gas supply vulnerabilities, transitioning from singular, gas/oil-reliant energy systems to multi-energy networks is imperative. Unlike conventional individual systems where devices are often oversized and underutilized due to being designed for demand peaks, a prosumer community can optimize device use, reducing both energy costs, investment overheads and ecological impact. Therefore, when properly designed and operated, prosumer communities mitigate the inefficiencies typical of traditional setups. However, achieving optimal design is challenging due to complex interactions among stakeholders. The economic and ecological aspects of prosumer communities need to be thoroughly investigated taking into account different scenarios, energy demands and building types. This project aims to investigate various case studies for prosumer communities in the Swiss scenario and explore the technological solutions that mostly benefit from energy sharing.
Time Resolved Photoluminescence Spectroscopy and Simulations
We are looking for a motivated Master Thesis student to join the Nanomaterials Spectroscopy and Imaging Group at Empa, located in the vibrant city of Zurich, Switzerland. Investigate carrier dynamics of cutting-edge optoelectronic materials, including thin films and 2D materials. Simulate Time Resolved Photoluminescence (TRPL) response. Fit experimental results and extract crucial optoelectronic parameters like diffusion coefficient, carrier concentration, and carrier lifetime. Gain hands-on experience in a dynamic research environment. Collaborate with leading experts in the field. Work on cutting-edge projects with real-world applications.
Internship, Semester Thesis, Master Thesis
Factors driving uptake of renewable energy systems in Swiss households
Development of an ML-driven Mobile App for Quality and Species Analysis of Roundwood
Roundwood is sorted by quality and species in the forestry (and in sawmills). Based on the dataset with images of roundwood (from partner sawmill³) containing quality and species labels, a classification model has been developed for predicting the species and the quality of a stem based on the image of its cross-section. The detailed description of the model architecture and the results can be found in the paper: https://www.sciencedirect.com/science/article/pii/S0957417423036217. The task of the project is to develop an iOS or Android App that based on the model results.
Enhancing Models for Roundwood Classification via Label Noise Correction
The project's goal is to optimize the processes in the wood industry through automation of a roundwood sorting into different quality grades based on image classification. The dataset comprises cross-sectional images of roundwood labelled with quality grades: B, C and D (B standing for the highest, D - the lowest quality) as well as tree species (spruce and fir). The implemented DL models provide 91% accuracy for the species classification task and 80% accuracy for quality classification on the cured data (no label noise). The goal of the thesis is to use the noisy data to improve the quality of the models.
Evaluate the robustness of data-driven controllers (ETH/Empa)
Performance of data-driven controller can be compromised corrupt data. This can have significant implications, especially in systems that rely on accurate data for decision-making. In this project, we will focus on robustness of data-driven controllers for applications in buildings.
Interpret data-driven control decisions (ETH/Empa)
System control interpretability is essential for user trust. This project will investigate the interpretability of in-house data-driven controller decisions. The objective is to improve transparency, thus facilitating their application in managing energy systems. By focusing on transparent control mechanisms, this research aims to bridge the gap between complex control strategies and user trust.
Control strategy development for energy exchange in a decentralized heating systems
The goal of this project is 1) to explore potential control strategies to manage the energy exchange for a decentralized, bidirectional district heating network and 2) to implement the most promising controller, in terms of complexity and effectiveness, in a simulation environment
Structurally Colored Aerogels
Structural color is a fascinating method employed in nature to achieve vibrant hues. Examples abound, from Iridescent opals to the delicate hues of butterfly wings, and the shimmering scales of beetles1 (Figure 1 a-c). Unlike conventional pigments, structurally colored materials boost resilience against photobleaching and can be easily designed to circumvent environmental and chemical hazards. This characteristic renders them an attractive sustainable alternative for various photonic applications.2,3 Renowned for their ultralow thermal conductivity and open pore structure, Aerogels find widespread use scenarios in thermal insulation, catalysis, environmental remediation, and optics.4 Among these applications, currently, thermal insulation stands out prominently, and an aerogel with intrinsic structural color holds the promise for sustainable and smart coloring endeavors.
Development of a dynamic supramolecular hydrogel from tumor dECM
We are looking for a motivated Master student to join Empa St. Gallen for this master thesis project. The candidate will be part of an exciting and collaborative project between the Particles-Biology Interactions Lab, the Biointerfaces Lab as well as the Biomimetic Membranes and Textiles Lab at Empa.
PhD position: Scanning Probe Spectroscopy Investigation of Molecular Quantum Spin Systems
We are looking for a highly motivated candidate with a strong experimental background in Solid State Physics, Surface Science or Quantum Nanoscience who wants to pursue cutting-edge research. In this project, you will synthesize and characterize strongly correlated quantum many-body spin systems using methods based on scanning probe microscopy. You will study local excitations at the single spin site level in bottom-up fabricated nanographene chains using a low-temperature scanning tunneling microscope. In combination with multiconfigurational simulations, such experiments will determine the energetics and dynamics of electronic and spin excitations in these strongly correlated quantum many-body systems. Obtaining precise and flexible control over spin sites and interactions will open ways toward the operation of carbon-based quantum spin devices.
Development of a Conceptual Framework for Resilience Assessment of Smart Energy Systems
In the era of climate change and growing global energy demand, smart energy systems have become pivotal in ensuring sustainable, efficient, and reliable energy delivery. These systems, characterized by the integration of advanced metering infrastructure, renewable energy sources, and innovative demand response technologies, form the backbone of modern energy strategies aimed at reducing carbon footprints and enhancing energy security. The Swiss Confederation, cognizant of these imperatives, advocates for a robust transition towards intelligent energy networks, setting the ambitious goal of a net-zero carbon economy by 2050. As we push the boundaries of energy system innovation, the imperative of resilience cannot be overstated. Resilience in this context refers to the smart energy system's capacity to anticipate, withstand, and recover from various forms of disruption like environmental phenomena, technical failures, or human-induced events. This project acknowledges the complexity and interdependence of the smart energy ecosystem, encompassing residential buildings equipped with the latest in energy-efficient technologies, user interfaces that allow for dynamic interaction with the energy grid, and decentralized renewable energy generation units that contribute to a sustainable energy mix. Electric vehicles (EVs), Heating, Ventilation, and Air Conditioning (HVAC) systems, and domestic appliances represent significant loads within the residential sector that can be managed to foster resilience. The bi-directional flow of energy in smart grids, facilitated by smart meters, allows for sophisticated energy management strategies that not only respond to system demands but also to user behaviors and preferences. The resilience of such an interconnected system hinges on its ability to maintain stability and operation despite unpredictable renewable energy generation patterns, potential cyber-physical threats, fluctuations in the energy market due to instability in the neighboring countries, and changes in user behavior. The Swiss energy paradigm provides an exemplary context for studying and enhancing the resilience of smart energy systems. By developing a conceptual framework for resilience assessment tailored to this context, this thesis aims to contribute to the body of knowledge that will empower stakeholders to design, implement, and maintain robust energy systems.
Non-Intrusive Load Monitoring and Customer Segmentation assisted demand flexibility provision in Swiss Households
Switzerland is committed to transitioning to a renewable energy system. The Swiss government has set a target of achieving net-zero carbon emissions by 2050. This will require a significant increase in the use of renewable energy sources. The Swiss power grid is also vulnerable to imbalances be-tween supply and demand. Demand flexibility can help to mitigate this risk and ensure the reliable operation of the power grid. Demand flexibility is the ability to shift or reduce energy use in response to changes in sup-ply or price. This is becoming increasingly important as the power grid transitions to renewable energy sources, such as solar and wind power, which are intermittent and less predictable. Demand flexibility can help to balance the grid and reduce the need for expensive and polluting backup power plants. Non-Intrusive Load Monitoring (NILM) and customer segmentation modeling are powerful tools that can be used to develop demand flexibility programs. NILM can be used to identify high-energy-consuming appliances and to track their energy usage over time. Customer segmentation modeling can be used to identify different groups of customers based on their energy consumption patterns. This information can then be used to develop targeted demand flexibility programs that are more likely to be effective for each group of customers.
Living materials as an alternative to antibiotics to fight against pathogen infections.
Wound infections present a significant challenge in healthcare, and traditional treatments involving antibiotics can lead to the emergence of antibiotic-resistant bacteria. Probiotics (i.e. the "good bacteria") have been studied widely for their potential antimicrobial effects and use in wound treatment as an alternative to antibi-otics. They have been reported to enhance wound healing, produce antimicrobial substances, disrupt biofilm, and restore the microbial balance in wounds. In this project, we aim to combine the benefits of probiotics and hydrogels to form a so-called "living hydrogel": i.e. a hydrogel with organisms inside. The living hydrogel can not only fulfill the function of a normal wound patch but also deliver the therapeutic factors secreted by the encapsulated probiotics to fight against pathogen infection and also promote wound healing.

Powered by  SiROP - the academic career network