This summer, check out some the interesting and inspiring journeys of ETH Zurich students who stepped outside the classroom and into innovation ecosystems around the world through ETH Studios.

From collaborating with Bloomberg in New York to exploring machine learning in the Swiss Alps, investigating extraterrestrial life with NASA, and reflecting on Europe’s tech future, these student-authored stories offer a unique glimpse into how ETH talent is shaping global conversations.

Here’s your curated summer reading list, straight from the ETH Ambassadors Blog:

1. SQL, LLMs, Bagels and Skyscrapers – A Journey of 5 ETH Students in NYC

By Maša Nešić, Maurice Hanisch, Eric Nothum, Vinícius Mohr, and Carlo Teufel

What happens when five ETH students step into the heart of the financial world for a 3-day tech challenge at Bloomberg’s New York office? A lot of learning, a lot of inspiration and just enough time for a bagel break. In their own words, “We meticulously worked on the project, exploring our team’s dynamics and attempting to put everyone’s skills to best use.”

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2. Bridging Innovation and Inspiration – TECH 2025 Heilbronn

By Giancarla Salzarulo

As part of the ETH delegation to TECH 2025 in Heilbronn, Giancarla reflects on the power of global dialogue, the challenges of scaling innovation in Europe, and why being part of ETH means more than just studying. She emphasizes, “I arrived with curiosity and left with inspiration. Being part of ETH Zurich’s story continues to be one of the greatest privileges of my life.”

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3. Mayhem in New York

By Noè Canevascini

What started as a spontaneous interview turned into a full-blown mentorship adventure in New York City. Noè’s story captures the unpredictability and opportunity that ETH Studio experiences can spark. He says, “Despite the challenges, this experience reinforced my love for tackling new opportunities and mentoring others.”

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4. Machine Learning Meets Geology: My Internship at SLF Davos

By Paulina Körner

At ETH Studio Davos, Paulina blended AI with earth sciences to explore how computer vision can detect borehole fractures, a step toward smarter, safer geotechnical work. She shares, “One of the highlights of my internship was the people I had the chance to work with. The team at SLF was made up of researchers and professionals from all over the world, each bringing a unique perspective to their work.”

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5. Learning About Extraterrestrial Life Detection at NASA JPL

By Marco Trentini and Adrian Fuhrer

How do you detect life on a moon of Saturn? During their seven-month stay at the NASA Jet Propulsion Laboratory, Adrian and Marco focused on developing instruments that can be used to detect life forms on other planets, particularly Enceladus, a moon of Saturn. Their work in the Chemical Analysis and Life Detection Lab aimed to understand and utilize the chemical processes involved in detecting life on other planets!

Read the story

ETH Studios

ETH Studios are global innovation outposts where ETH students tackle real-world challenges alongside companies, researchers, and startups. Whether in New York, Heilbronn, Davos, or at the experimental StudioX, students gain entrepreneurial and interdisciplinary experience while contributing to sustainable and tech-driven solutions.

Contact Francesca Caggiula at eth-studios@ethz.ch if you are interested in more information on and about the ETH Studios.

Happy reading!

My name is Luca Baumann, and I am a Master student in Data Science at ETH Zurich. During my Bachelor’s degree in Electrical Engineering and Information Technology, I discovered my passion for Machine Learning and working with data. Since Data Science combines both aspects, I decided to continue my studies in the specialised Data Science master’s degree. However, since many courses at ETH Zurich heavily focus on theoretical principles and practical applications are often slightly more neglected, it is crucial to work on hands-on projects. Hence, the Internship at PMOD/WRC was the perfect opportunity for me to continue working on my skills and gather valuable practice experience by working with real-world data. This perfectly aligns with my career aspirations. After my studies I would like to work as a Data Scientist or Machine Learning Engineer. 

What impressed me most about my time at PMOD/WRC was its long-lasting history. Many of the components of the used satellites are available in PMOD/WRC’s own museum and one could see the technological advancements of early versions of satellites compared to new ones. This was particularly useful to grasp a better understanding of the satellites and to understand where on the satellite which data was measured. Additionally, everyone in the team was very welcoming and helpful which made interactions and collaborations very pleasant. 

Another impressive aspect of my Internship in Davos was the amazing view on the train ride to and from Davos as well as in Davos itself. Switzerland has so many beautiful nature landscapes and I think especially as a Swiss Citizen this gets frequently forgotten because we take it too much for granted. 

Personally, I learned so much from my time at PMOD/WRC. It combined many important tasks like data preparation and cleaning, as well as model training and evaluation. Each of these tasks are part of the daily business a Data Scientist must deal with. I am deeply grateful for this opportunity! I think this internship experience helped me prepare for my later career, and strengthened my conviction to pursue a career in Data Science.

About PMOD/WRC

One of the trickiest acronyms in the ETH Zurich ecosystem, PMOD/WRC stands for “Physikalisch-Meteorologisches Observatorium Davos / World Radiation Center.” It is a leading Swiss research institute dedicated to studying solar radiation and its influence on Earth’s climate. As a designated calibration center for the World Meteorological Organization, PMOD/WRC develops high-precision radiometers for both space-based and ground-based applications, ensuring global consistency in solar irradiance measurements and supporting international climate monitoring efforts. Find out more on their website: https://www.pmodwrc.ch/en/home/

Hello, dear blog reader! My name is Noè.

Six years after starting my studies at ETH, I am now almost finished. I had to take some exams again, I think the professors liked me so much they decided to keep me around for another year. Before officially diving into adulthood and hopefully a career in cybersecurity, I decided to squeeze in an internship. However, just as I was about to start, an intriguing job post caught my eye on LinkedIn: “Supervise Swiss ICT Talents in New York City.” A month in NYC? Supporting a group of ambitious 18-year-old apprentices? Count me in!

To get the job, I had to convince the organizing team at TIE-International. Luckily, I was already in Zug teaching a programming course and met the organizer there for a quick chat. That chaotic week included a paper deadline (later rejected, but we’ll revise and try again), the job-interview, the class, and a nasty stomach bug. Somehow, I survived it all and got the job.

The most challenging part came before even arriving in NYC: finding projects for the apprentices. My initial contacts fell through — either people had left their companies or the projects had moved elsewhere. I turned to friends in NYC, but most worked in large corporations where onboarding alone could take a month. In the end, the apprentices landed at lean startups with manageable side projects. My girlfriend came to the rescue, connecting me with someone who posted in a Slack group for B2C startups in NYC. Within days, I went from scrambling for projects to turning offers away due to my limited capacity.

Once in New York, the city’s scale was overwhelming. Anything that was at least a bit famous—whether entering the city, visiting Katz’s Delicatessen for its famous pastrami sandwich, or grabbing a slice of pizza at some of the more famous spots—required waiting in line for hours. Despite this, the energy of the city was undeniable. Every day, I met someone with a startup idea or an ambitious project. The air is ripe with opportunities, ready to be caught by those willing to make a leap of faith and grab them. However, it was clear that it isn’t that easy: I was surprised to find many CS graduates working as baristas or receptionists in coworking spaces, struggling to find jobs in their field.

What I truly enjoyed was working with the apprentices, and all of the people that made this event possible. They were ambitious, curious, and full of ideas. Some knew exactly where they wanted to go, while others were still figuring it out—both paths are perfectly fine. What surprised me most was how much they seemed to appreciate my support. They often asked me to join their activities or sought my help, making me feel valued in ways I didn’t expect.

Despite the challenges, this experience reinforced my love for tackling new opportunities and mentoring others. NYC reminded me to be brave, ask for what I want, support those around me and try to be there for them, the rest will follow.

Interested in ETH Studios? Discover more here.

I recently had the opportunity to intern at ETH Zurich’s Studio Davos/SLF, working on a project that blends geology with machine learning. My background is in environmental sciences, and during my master’s, I developed an interest in applying machine learning to solve real-world environmental problems. While I had worked on projects such as predicting the biodegradability of chemicals, computer vision was relatively new to me. This internship allowed me to explore it further while tackling a critical problem: identifying fractures in borehole imagery.

The project I worked on was focused on advanced fracture identification in borehole imagery through semantic segmentation. While this may sound technical, its significance spans several industries. Boreholes are drilled into the Earth for various purposes, and understanding the fractures and changes in the surrounding rock mass is crucial for making informed decisions about construction safety—whether for tunnels, dams, or even storage facilities for hazardous materials. Understanding how fractures form and evolve, especially in response to factors like ventilation or pressure, can significantly improve safety and efficiency in such projects.

The main challenge of the project was the need for more labelled data. Although there are plenty of borehole images, there is a scarcity of labels that help us differentiate between different types of fractures. Therefore, my initial task involved learning how to identify and label these features accurately. Although labelling borehole images might not seem thrilling, it is critical for improving the model. Once we expanded the dataset and refined certain structural aspects of the model, we observed exciting advancements in its predictive capabilities.

One of the highlights of my internship was the people I had the chance to work with. The team at SLF was made up of researchers and professionals from all over the world, each bringing a unique perspective to their work. Whether it was in geology, environmental science, or avalanche monitoring, the diversity of expertise made every conversation an opportunity to learn something new. Working in Davos also enhanced my overall experience. Whether swimming in the lake during lunch breaks or going on after-work hikes or bike rides in the mountains, the combination of fresh air, exercise, and stunning views made Davos an incredible place to live and work.

Overall, my internship at SLF not only gave me hands-on experience in computer vision but also broadened my understanding of how machine learning can make a real-world impact, even in fields I hadn’t considered before. Moving forward, I’m excited and motivated to continue exploring the intersection of environmental science and machine learning.

Interested in ETH Studios? Discover more here.

I first became aware of the ETH Studios projects at a meeting where ETH researchers presented their work to students. I was immediately intrigued by the prospect of working on a research project in the picturesque setting of Davos, a place I had so far only associated with skiing and the World Economic Forum.

As an applied mathematics student with an interest in using statistics and machine learning for environmental sciences, I found the perfect project: modelling river-runoff at the Snow and Avalanche Research Institute (SLF). The relevance of this task could not be more evident. With floods becoming increasingly frequent, studying their evolution under different climate scenarios is crucial. To achieve this, capable models that can use weather data to predict river levels are essential. Davos seemed like the ideal location to study rivers and streams, with its abundance of water and the lingering reminders of the severe 2005 flood in neighboring Klosters underscoring the importance of the task.

As I rode the train up to Davos, Zurich was already on the brink of spring, but the higher elevations told a different story. Snow piled up along the tracks, and sunshine was scarce. The first few days were filled with snow and a wintry mood in town, but eventually, the sun broke through, revealing breathtaking views from the office. I enjoyed having lunch outside and taking walks in the surrounding valleys.

I was warmly welcomed at SLF,  quickly getting to know my colleagues from the institute as well as visiting researchers from abroad. The communal lunches in the institute’s small cafeteria provided a cosy opportunity to speak to researchers from various backgrounds.

One highlight of my stay was a tour of SLF on my final day in Davos.  The variety of research conducted at the institute, from field-testing the effects of vegetation to advanced modelling of rockfalls and avalanches, was quite intriguing. During the tour, we visited the cold rooms on site, where researchers work at temperatures as low as -25 degrees Celsius to analyse snow samples from around the world. Our guide showed us his workstation, including a snow-making machine and an avalanche simulator.

Meanwhile, the project progressed rapidly, and as I returned to Zurich to continue my work remotely, we already had the first model results to analyse. It quickly became clear that machine learning is very well-suited for modelling rivers in the Swiss domain, predicting even extreme events with impressive accuracy and significantly outperforming state-of-the-art models. This opens up exciting possibilities for future modelling: better precision and faster inference mean that changes in river levels, floods, and droughts under climate change can be more accurately studied.

A good understanding of these changes is of great importance for hydropower generation, flood defences, and climate adaptation. While additional work is needed to ensure the reliability of machine learning models, even in a changing climate, the future is promising.

Interested in ETH Studios? Discover more here.

During our seven-month stay at the NASA Jet Propulsion Laboratory, we focused on developing instruments that can be used to detect life forms on other planets, particularly Enceladus, a moon of Saturn. Our work in the Chemical Analysis and Life Detection Lab aimed to understand and utilize the chemical processes involved in detecting life on other planets!

Enceladus is unique because it consists of an underground ocean covered by a thick ice layer. The hypothesis that this ocean might harbor life is based on the assumed presence of hydrothermal vents on its seabed, similar to those on Earth. In our project, we developed mechanisms that enable the collection of liquid samples from an underwater environment. Particular challenges included creating space-compatible electronic boards that can withstand extreme conditions such as radiation, temperature fluctuations, and strong vibrations during rocket launches.

In addition to the technical work, our stay in California also offered ample opportunities for personal development. We used our free time for excursions to Yosemite National Park, Disneyland, the Kennedy Space Center in Florida, and the Carrizo Plain National Monument during its bloom period. These activities, combined with interactions with colleagues and experiences in the American work culture, have profoundly influenced our perspective on life abroad and the privileges of living in Switzerland.

The opportunity to work at the Jet Propulsion Laboratory was an invaluable experience that expanded both our technical skills and personal perspectives. The insights and experiences we gained during our stay will have a lasting impact on our future projects and career paths.

Interested in ETH Studios? Discover more here.

The task sounded complicated to begin with: use the methods of machine learning to create a program that could classify certain small scale features in the atmosphere of our Sun. These features we are interested in are so called solar jets, a collimated ejection of plasma created by magnetic recombination. For this I worked at PMOD, the “Physikalisches Metorologisches Observatorium Davos” in Davos Dorf. Here I would meet experts from the institute that could tell me everything about the solar jets as well as professional AI engineers from Lab42, a small company based in Davos, to answer all the questions about AI I would ever have.

Even with all these resources the task would not be easy. For one, I myself have never worked with methods of machine learning and the other thing is that even the experts on solar jets are often unsure if they are looking at a solar jet or not, so how is an AI supposed to distinguish between them?

The good news is that I was not alone with this task. We were a total of three master students working on this project together: Together with Michel, whos previous experience in AI engineering would proof to be extremely helpful, and Remy, who is among many things a talented programmer,  we would start to familiarize ourselves with the task we faced as soon as we arrived in Davos.

First we met with the experts on solar jets to learn about the physics behind the process we aim to classify. After all, we are all physics students. In a second big meeting, we then met with Hansueli, our expert AI engineer from Lab42.

After a warm welcome at Lab42, he lead the way to their conference room. It was a bright open room with a bay window and a massive circular wooden table in the middle, where the likes of Napoleon have dined before. In the corner of the room by the window was the biggest and possibly brightest brain I have ever seen. The illuminated artificial brain rested on a transparent pedestal which was covered in signatures by people who have visited this place before. Besides the brain was an orange banner and on this banner was a pattern of hands, interlocked with one another to form a brain. This brain is the very embodiment of Lab42’s promise, the decoding of the mind, for all of humankind.

One of the first questions Hansueli asked us that day was, what we think what intelligence is. It is surprisingly difficult to grasp, as it comes in many different forms. Is the the ability to adapt, to improvise or merely to be self aware? From that day on I had many interesting discussions with friends and family on that very topic.

While our goal is neither as grand nor as noble as the goal of Lab42 it feels just as daring as theirs. But as a team and with the help of Lab42 and PMOD I am optimistic that we can do it.

Interested in ETH Studios? Discover more here.

When Henrik first approached me about a project aiming to detect solar jets — short-lived plasma beams ejected from the coronal region of the sun—using artificial intelligence methods, my initial reaction was scepticism. What does AI have to do with such physical processes? At first glance, my scepticism seemed justified—the topics appear unrelated altogether!

I had the opportunity to take a deeper look alongside two fellow physics master students, Michel and Henrik (their recollections are also detailed on this page), at the physical-meteorological observatory in Davos (PMOD). Our task was to develop a proof of concept for detecting these small solar features. And a deeper look we got: during our two weeks in Davos, we encountered nearly every roadblock imaginable in utilizing astrophysical photometry data in machine learning pipelines.

This made our intermediate result all the more satisfying: a neural network trained solely on observational data to detect solar jets. The concept actually makes a lot of sense since the jets cannot be modeled analytically, being inherently irregular. This means they are detectable only by the human eye, which is exactly the approach neural networks seek to replicate.

Overall, this project has been an incredible learning opportunity, even for our own “neural networks” (our brains), as it allowed us to become more familiar with this emerging technology and the paradigms associated with it.

Our coding endeavors were complemented by a healthy dose of snow, which we got to enjoy on the weekend (and more cautiously during our walk to work). Additionally, we were fortunate enough to secure a flat for the three of us, making us roommates for the duration of the project. This was a great opportunity to spend some time together in a more relaxed atmosphere, including cooking, a movie night and even a home-workout. So, beyond the scientific work we had a fantastic time in Davos, leaving us motivated to finalize this project in the upcoming weeks—hopefully yielding conclusive results.

Interested in ETH Studios? Discover more here.

Hi! I’m Jessie, a computer science student currently in my fifth bachelor semester. I’m interested in both data science and the environment, so when I saw this opportunity, I thought there couldn’t be a better match. The idea of the project is to determine the effects varying degrees of solar irradiance have on the climate. The influence of certain climate factors is predicted by running huge simulations on supercomputers of our earth, divided into grid boxes, while changing parameters. Then, we analyze the data to understand the impact of different variables, mostly by doing time series analysis or Principal Component Analysis to try to detect noticeable differences and patterns.

When I arrived in Davos, I was stunned by how beautiful the city looked. It snowed heavily throughout my stay so streets were covered in snow and there were Christmas lights everywhere. It looked like something straight out of a fairytale. The World Radiation Center, situated on a hill, offered a cozy ambiance along with a beautiful view of the city. The institution is an international calibration center for meteorological radiation measurement instruments, so scientists from all over the world come to visit. Observing the sophisticated instruments that are used for the continuous monitoring of solar irradiance was very interesting.

The researchers at the center were very passionate and knowledgeable about their field, and also very helpful. I did not have a background in environmental sciences or physics, so at first, I was very confused about how to evaluate climate data, since they were calculated based on physical indices. However, Jan and Timofei took the time to explain the physical principles underlying our current understanding of the Earth, and it was very interesting to learn how many phenomena are explained through science, but also which ones we are still unable to explain.

One of the highlights was an event called the ‘Scientist Beer’ in Davos. I attended a talk by a renowned scientist on space exploration and the stars, which rekindled my childlike sense of wonder and immersed me in a field I knew little about. That night was a reminder of why we dive into science in the first place – that pure curiosity and the thrill of discovering the unknown.

Throughout this internship, I’ve learned so much about the complexities of Earth’s weather and ecological phenomena, our current understanding, and the areas that remain mysterious. But most importantly, I’ve been immersed in a scientific environment that has taught me about the essentials for a successful career in science, why some choose academia over industry, and the crucial importance of continuous climate research. This experience has profoundly shaped my perspective and future aspirations in the field of environmental data science.

Interested in ETH Studios? Discover more here.

From the bustling streets of Zurich to the towering skyscrapers of New York City, our journey with TIE-INTERNATIONAL was a unique experience. Supervising apprentices from various Swiss companies, I found myself amid a dynamic, fast-paced world that vastly deviates from Zurich.

Our journey started with a first week of sightseeing, where we explored New York. We visited known places like Time Square, Central Park, and Ground Zero. Additionally, we went to an NBA and NHL game where we witnessed American sports and fan culture, which deviates significantly from the European culture. Next to touristic activities, we also gained first insights into the work life at the New York Stock Exchange and UBS, where we visited the trading floor and the IT department.

After exploring and settling in the city, we started to work in the Big Apple. Initially, we faced the challenge of a small workload, which rapidly transformed into too many job opportunities. However, the apprentices managed the intense workload very well. Furthermore, the work allowed us to meet multiple inspiring and intriguing personalities. Like the founder of Beem, a virtual reality start-up, or Swiss representatives at the Swiss Consulate of New York. Their openness and warm welcome helped to make our transition into American work life more manageable.

However, working in New York exhibited multiple cultural differences, such as meetings tending to start at a different agreed-upon time. One key takeaway from our trip is to remain flexible in the daily schedule, as changes are more ordinary than in Switzerland. The flexibility and adaptability we gained will serve the apprentices and myself well in the future.

One of our most memorable experiences was the Halloween parade. We witnessed a spectacular display of creativity and culture, which truly characterizes the city’s spirit.

Contrasting to life back in Zurich, New York City, especially areas like Chinatown, became a newfound favorite. Its streets, filled with an array of sights, sounds, and flavors, offered a glimpse into the city’s cultural diversity. Additionally, it provided a different set of cuisines in contrast to the traditional American fast food.

Reflecting on our time in New York, it’s clear that the city’s dynamic was both a challenge and an opportunity for growth. Returning to Switzerland, I thank the people who helped make this trip possible. It was an unforgettable month of learning and rich experiences, and I am happy that I was able to contribute to the journey.

Interested in ETH Studios? Discover more here.