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The Intern will be recruited for a research project on trace metals in agricultural soils. Specifically, we are looking for an intern to support a doctoral student in the laboratory for soil analyses. You will receive salary, intense training in the preparation of soil samples for chemical analyses, wet chemistry, data management as well as data analyses and quality control procedures using ICP-MS. These tasks require a reliable working style to assure that the data is of high quality and an active communication to coordinate with the PhD student. You will be part of two international and collaborative research and PhD teams from the Group of Plant Nutrition. The group frequently meets for scientific exchange which will facilitate your integration into the team. For the internship, you will receive support from the supervisors and members of the Group of Plant Nutrition. The project will be mostly conducted at ETH’s Research Station for Plant Sciences that also offers opportunities for affordable housing.
Questions? Please contact us. Interested? Please send a CV, a short motivation letter, and diploma or transcripts from your ongoing BSc or MSc studies.
- Crop and Pasture Production, Soil and Water Sciences
- Internship, Student Assistant / HiWi
| We offer the unique opportunity to be a part of a dynamic award-winning start-up team and to develop a live-saving therapy that will change the medical landscape. You will have the chance to get hands-on lab experience with nanomaterials and to apply your knowledge accumulated during your studies. Additionally, you will gain a deeper insight into the medical device industry. Besides an exciting and modern work environment at Bio-Technopark Schlieren, a flat hierarchy, room for growth and an independent working style are amongst the core values of our startup. - 1.2 Computer and Information Sciences, 2.2 Electrical- , Electronic-, Information Engineering, 2.3 Mechanical Engineering, 2.6 Medical Engineering, 2.11 Other Engineering and Technologies
- Internship
| hemotune AG is a Swiss medical device start-up company originating from ETH Zurich. Our mission is to develop a life-saving breakthrough medical device for targeted blood purification, and we are currently in the preclinical development phase. To support our biotech team, we are looking for a:
- 1.4 Chemical Sciences, 1.6 Biological Sciences, 2.4 Chemical Engineering, 2.5 Materials Engineering, 2.10 Nano-technology, 3.4 Health biotechnology
- Internship
| In dieser klinischen Studie werden jugendliche Patienten mit Skoliose einer Röntgenuntersuchung unterzogen. Anschliessend werden optische 3D Aufnahmen der Rückenoberfläche in verschiedenen Haltungen und Bewegungen aufgenommen. Die Ergebnisse aus den optischen 3D Aufnahmen werden in der Datenauswertung mit den klinischen Parametern aus der Röntgenauswertung verglichen. - Biomechanics
- Internship, Master Thesis
| Cell-based therapies have emerged as a powerful platform for treating pathological phenotypes [1]. A focus of synthetic biology is to engineer cellular systems that can act by releasing therapeutic effectors to mitigate disease states [2]. Developing such circuits remains a great challenge. The goal of this project is to engineer genetic circuits in human cells and establish cell lines for therapeutic applications. Within this task, the prospective student may explore different genetic topologies and develop various cell line engineering workflows and co-culture assays. - Biotechnology, Engineering and Technology
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| The project is devoted to development of new generation sensors for human bodily fluid biomarkers. The main aim is development of compact and non-invasive modified electrodes for electrochemical sensing of these important compounds. - Analytical Chemistry, Biosensor Technologies, Electrochemistry, Medical and Health Sciences
- Master Thesis
| The goal of the project is to develop a simple and versatile method for production of robust conductive patterns on textile via deposition of conductive polymers. This technology will allow further development of wearable electronics for biomedical applications. - Chemistry, Medical and Health Sciences, Polymers
- Bachelor Thesis, Semester Project
| The aim of the project is to investigate the benefits, requirements and drawbacks of physics informed neural networks in the context of personalised cardiac and cardiovascular models - Biomechanical Engineering, Clinical Engineering, Computation Theory and Mathematics, Fluidization and Fluid Mechanics, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Simulation and Modelling
- Master Thesis
| There has been a rapid acceleration in the expansion of electrolysis capacity in recent years. The previous year marked a record-breaking deployment of electrolysis technology [1]. Recovering waste heat from electrolysis and compression can improve the overall system efficiency. The integration of such waste heat into district heating systems has been investigated in literature [2], where levelized cost of heat has been used to value waste heat. However, given dynamic electricity price, time-varying hydrogen demand, potential provision of ancillary services to energy systems, time-varying thermal demand within the district heating network and the supply temperature level, the marginal cost of waste heat can vary during the day. In addition, base heat supply systems such as heat pumps are equipped to supply the heating demand. Therefore, the pricing of waste heat from a hydrogen-based system needs to be lower than the pricing of heat from heat pumps, to be accepted by consumers. - Civil Engineering, Electrical and Electronic Engineering, Environmental Engineering, Interdisciplinary Engineering
- Master Thesis
| In modern society, the problem of traffic congestion in densely populated cities is worsening due to the heavy daily commuting. This affects not only the commuters that waste many hours in traffic congestion every year, but it also creates inefficiencies and pollution that translate into additional societal costs. The role of service stations in the future years will gain importance due to, among other factors, the constant raise in electric vehicle sales. The presence of a service station on highway stretches highly affect the level of traffic congestion on the road. In this work, we aim at developing an Iterative Learning Control scheme that is able to maximize the positive effects that a service station has in terms of peak and overall traffic congestion reduction. We will validate the designed algorithm using real data and state-of-the-art micro-simulators.
- Automotive Engineering, Control Engineering, Systems Theory and Control
- Master Thesis, Semester Project
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