ETH Zürich has huge a campus in Switzerland and widely known as for its contribution in top notch education and research. The contribution of ETH Zürich is not only limited to natural sciences and engineering but it also offers high quality research as well as higher education in bio-medical sciences, social sciences, humanities, psychology, education, architecture etc.

1. Doctoral Student of Dairy Nutrition

Summary of Doctoral Project:

The Group of Animal Nutrition is seeking a motivated, team-oriented person with a strong interest in the interface of basic and applied research in agricultural and nutrition sciences to enhance understanding of nutrient utilization efficiency and improve the sustainability of livestock farms. You are expected to conduct interdisciplinary research in the area of dairy nutrition. Affinity for animal experiments and laboratory work is essential. 

Last Application Date: Open until filled

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2. PhD Position in the field of development of machine learning technologies and their deployment in the wood industry

Summary of Doctoral Project:

The WoodTec group combines the expertise of scientists in the fields of wood engineering, machine learning and chemistry to open up new application fields for wood products and to develop solutions for a more efficient use of wood. The goal of the project is to build a framework that includes a non-destructive method based on high-resolution images and structured data for quality and strength grading of wood. The candidate will work on developing machine learning models, implementing them, and building machine learning pipelines. The research activities are conducted in a joint working group between WoodTec, Laboratory for Cellulose & Wood Materials, Empa & DS3Lab: Data Sciences, Data Systems & Data Services, ETH.

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3. PhD Position: Dissection of the molecular crosstalk between bacteria and fungi

Summary of Doctoral Project:

Multicellular fungi are exposed to numerous antagonists including competitors, parasites and predators. Compared to other multicellular eukaryotes, our knowledge about the defence mechanisms of multicellular fungi against their antagonists is scarce. In the group of Markus Künzler, we use reductionist and experimental approaches to identify and characterize these mechanisms at a molecular level. Special emphasis is put on fungal defence mechanisms against fungivorous nematodes and bacterial competitors. Preliminary results of confrontation experiments of the model mushroom Coprinopsis cinerea with model bacteria suggest that this fungus can sense the presence of bacteria via molecules that are secreted by the bacteria. As a response to these signal molecules, the fungus appears to be able to specifically induce genes coding for antibacterial effector molecules.

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4. PhD candidate in Catalysis, Surface Chemistry and NMR spectroscopy

Summary of Doctoral Project:

The project addresses one of the key challenges in modern heterogeneous catalysis, namely understanding the structure of the active sites by direct probing them via state-of-the-art solid-state NMR techniques. In the context of sustainable chemistry, metal-doped zeolites have shown great potential for industrial applications; yet their development is typically impeded by the difficulty to establish detailed structure-activity relationship due to the lack of information about their active site structure. The main challenge will comprise the generation of well-defined metal-sites on zeolite surface using SOMC approach and the development of NMR techniques for observation of these sites and their surrounding by advanced spectroscopic techniques, in particular solid-state NMR. The ultimate goal of the project will be understanding the reactivity of these sites in industrially important reactions using parameters of an NMR lineshape as descriptors for the electronic state of the active sites.

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5. PhD position in Digital health technologies for upper limb rehabilitation

Summary of Doctoral Project:

In case of acquired brain injury (stroke, traumatic brain injury) and spinal cord injury, and despite recent significant progress in acute care and inpatient NR, 60% of patients still suffer important sensorimotor and cognitive deficits following discharge. Therapy thus has to be pursued at home during the chronic phase, but the suboptimal transition between inpatient and outpatient NR and the unavoidable decrease of therapy dose after discharge highly limit the progress margin of recovery. Composed of clinicians, research institutions and industrial partners, the SwissNeuroRehab consortium aim at developing a continuum of care paradigm, with proper transitions between clinical and home environments and a suitable model for home therapy.

Last Application Date: Open until filled

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7. Doctoral Student in Production and Operations Management

Summary of Doctoral Project:

We offer a full-time research position with a competitive salary in accordance with ETH standards. You will become part of an ambitious, young research team offering an outstanding research environment and team spirit. The candidate will be involved in the teaching and supervision of bachelor and master’s students. The average duration for a doctoral student at D-MTEC is four years. The starting date is flexible. The working language is English. ETH Zurich rules apply.

Last Application Date: Open until filled

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8. Doctoral Student “AI in Manufacturing”

Summary of Doctoral Project:

This position focuses on AI in Manufacturing with the aim to further our research on using AI in process improvement/quality management. Interested applicants could check out the ETH news article Improving quality through artificial intelligence. We study applications and effects of AI in factories.

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9. PhD Positions in Electronic Design Automation and Reconfigurable Computing

Summary of Doctoral Project:

We are interested in developing a broad scope of techniques to ease the programmability of digital hardware (e.g., reconfigurable devices such as FPGAs). Our goal is to bridge the gap between software and hardware by developing language abstractions, compiler flows, and hardware devices that enable software developers from different domains to accelerate emerging compute-intensive applications. We are looking for creative and highly motivated researchers to join our team. Each new group member can choose a research direction according to their background and our mutual research interests. Apart from actively shaping our group’s research, the PhD positions include international collaborations with academia and industry, mentoring BSc and MSc students, and teaching activities in the areas of electronic design automation, reconfigurable computing, and embedded systems.

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10. Doctoral Candidate – Evaluating sustainable food systems

Summary of Doctoral Project:

The project objective is two-fold: (i) to improve and/or develop sustainability evaluation methods in the realm of life cycle assessment, prospective life cycle assessment, scenario projections, or integrated modelling, and (ii) to develop recommendations for sustainability improvements in different supply chains, countries, and regions, based on quantitative analyses. An additional focus will be on future foods and alternative proteins (e.g., plant-based foods, cultured meat, insects, and microalgae) in collaboration with EU partners. The position is fully funded.

Last Application Date: Open until filled

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11. PhD Position in Observational Earthquake Seismology

Summary of Doctoral Project:

One major obstacle for understanding the physics of earthquakes is that, usually, earthquake phenomena can only be observed from large distances, where much information has already been lost to seismic attenuation. Next-generation underground laboratories, like the recently built Bedretto Underground Laboratory for Geophysics and Geoenergies (BULGG), address this challenge in that they facilitate in-situ, short distance obser­va­tions for experiments under natural crustal stress and hydro-mechanical con­di­tions. Building on the improved monitoring conditions these labs provide, we can potentially tackle long-standing fundamental science questions that have been difficult to address in more conventional settings (e.g. on the origin of high frequency radiated seismic energy or on the role of aseismic deformation around seismogenic faults). To make full use of these observational opportunities, however, we need to develop a new generation of monitoring and inference methods.

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12. Research Assistant: Event-Based Smart Sensors for Embedded Systems and Autonomous drones

Summary of Doctoral Project:

The group is looking for a talented and motivated master student willing to start as a Research Assistant in an emerging topic with an eventual possibility to study as PhD student after one year in the topics of event-based cameras, Spiking Neural Networks, Tiny Machine Learning, Embedded system, and Drones. The PhD position will be co-hosted with the new D-ITET Center for Project-Based Learning for the teaching activities and the coordination of an EU project.

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13. PhD position – Applications of electrochemistry in air quality field

Summary of Doctoral Project:

The research is related to applications of electrochemistry in the field of air quality. Electrochemistry is a powerful tool to probe chemical changes and control chemical reactions. Our group is engaged in development of various electrochemical sensors targeting gaseous and biological pollutants. We also work on electrochemical conversion of harmful gases. We are looking for suitable candidates with a master level degree in chemistry, chemical engineering, electrical engineering, material science or related fields with excellent grades. Good experimental capability is of high value. Good command of English is required.

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14. PhD position: global modeling of soil sulfur cycling

Summary of Doctoral Project:

Sulfur is an essential macronutrient to plants and of key importance in safeguarding crop yields. Its bioavailability depends on complex interactions between atmospheric replenishment, soil properties and biogeochemical transformations. Our goal is to advance the understanding of the key processes driving concentrations and chemical speciation of sulfur in soils, and of how the sulfur cycling through the soil-plant-atmosphere system will shift under climate change.

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15. Ph.D.: Clinical Data-based Machine Learning Diseases Modeling on SCI Conditions

Summary of Doctoral Project:

Conditions such as pressure injuries, autonomic dysreflexia, and other cardiovascular conditions are highly prevalent affecting large portions of the SCI population, representing a huge risk for the patient’s health and the healthcare system. You would join a team of clinical and research scientists in the task of improving the long-term prognosis of Spinal Cord Injury (SCI). In this project, we are working with multimodal and heterogeneous data from diagnosis, physiotherapy, clinical interventions, physiological measurements, body metrics, robotics rehabilitation, among many. We are developing advanced methods for feature extraction, data integration, and clustering from this growing body of clinical data. We will extract and analyze a large amount of information from longitudinal multi-modal clinical data (clinical systems and embodied sensing studies), to model the conditions and risk factors for making predictions about disease phenotypes, and disease progression.

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16. Ph.D.: Machine Learning and Sensing Technologies for Personalized Healthcare of SCI individuals

Summary of Doctoral Project:

Conditions such as pressure injuries, autonomic dysreflexia, and other cardiovascular conditions are highly prevalent affecting large portions of the SCI population, representing a huge risk for the patient’s health and the healthcare system. You would join a team of clinical and research scientists in the task of improving the long-term prognosis of Spinal Cord Injury (SCI) through physiological and clinical data fusion for embodied sensing of SCI individuals. This work within a clinical setting at SPZ will bring you close to intelligent health management while exploring multiple data and sensory systems. This project is embedded within the framework of lifelong medical and social care where wearable and nereable sensing will enable us to address the challenge of continuous behavioral and physiological monitoring. Sensors can be used to continuously and unobtrusively identify relevant digital biomarkers and objectively assess disease progressions, providing feedback, and ultimately construct models of the conditions for preventive care.

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17. Doctoral position on Evidence-Informed Policymaking

Summary of Doctoral Project:

Methodological and technological progress in measuring the impact of policies has greatly improved the quality and amount of data available for designing effective policies to reduce global poverty and inequalities. Yet, many policymakers and practitioners often do not systematically use available evidence to address policy problems. Recent research has shown that low uptake of scientific evidence for policymaking is also (even if not solely) linked to decision-making biases, lack of statistical training, mistrust in science, and data presentation formats. In this research project, we want to leverage insights from the learning sciences, decision-making sciences, and development economics to create new knowledge and tools that support policymakers around the world to use scientific evidence for policymaking.

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18. PhD Position in Security Politics

Summary of Doctoral Project:

The CSS research group is aiming to conduct excellent, innovative, and politically relevant academic research on contemporary security issues; to offer expertise through engagement with practitioners and the public based on this research, and to provide high-quality teaching to both academic-​ and practice-oriented students. Our research is theory-driven, empirically grounded, and broad in terms of methodology. We focus on changing threats to states and their societies, and how key actors organize themselves to address these threats. A sustained focus on causes and consequences of political violence, on shifts in security thinking, and on the institutions, political processes, norms, and policies to mitigate insecurity defines us. Security Studies is inherently inter-and transdisciplinary: We draw on approaches from international relations, security and strategic studies, international history, political sociology, political psychology, and criminology.

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19. Internship: implementation of a robust and extensible logging library for cryostats

Summary of Doctoral Project:

Our lab primarily studies microwave-frequency superconducting circuits, which are one of the most promising physical implementations of quantum bits (qubits), the fundamental building block of quantum computers. To function reliably, the qubits must be cooled to temperatures as close to absolute zero as possible and shielded from room-temperature electromagnetic noise. To reach this particular operating regime, we use specialized cryostats that employ a helium dilution cycle to cool the samples down to millikelvin temperatures. Since our experiments rely on low temperatures to function correctly and the cryostats are complicated mechanical systems, we must monitor the status of several system metrics 24/7 so that we can react to any anomalies. We currently log metrics for each of our 10 cryostats separately but are looking to unify our logging codebase to reduce the maintenance burden and share new features among all of the systems.

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20. PhD Position at the Nexus of Economics and Security

Summary of Doctoral Project:

The global landscape is characterized by a growing number of issues at the nexus of security and economics. The US-China strategic rivalry, the emergence of new dual-use technologies, and the impact of the COVID-19 pandemic on global supply chains have increasingly drawn policy makers’ attention to this nexus. Governments have started to “weaponize” supply chains, to form new types of strategic partnerships with other states, and to come to terms with the growing (geo)political power of technology companies. Yet, Political Science scholarship provides only limited insights into the implications of the changing relationship between these economic and security issues, so far.

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21. PhD position: Novel approaches to understand orthopaedic deficits in Cerebral Palsy

Summary of Doctoral Project:

We focus on the study of kinematics and kinetics in healthy, reconstructed and replaced joints. By examining the quality of movement, we also aim to extract key information on an individual’s functional status and thereby lay the foundations for understanding and monitoring the degenerative changes that occur with musculoskeletal and neuromotor pathologies, but also the adaptation that results from ageing or rehabilitation. The targeted application of key experimental and computational techniques thereby enables encompassing approaches to support clinical decision-making in the fields of gerontology, trauma, orthopaedics and neurology, but also opens perspectives on the objective assessment of both medical technologies and therapies alike.

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22. Ph.D. candidate for developing, modelling, and optimising new concepts for high-power pulse generators for geothermal energy

Summary of Doctoral Project:

We are looking for outstanding, highly motivated individuals interested in pursuing Ph.D. research in the interdisciplinary area of pulse generator (modulator) systems. The research topic focusses on the development of new concepts for pulsed power modulators, which should generate pulses with a very fast pulse rise times (<100ns), with a pulse amplitude in the range of hundreds of kilovolt, and with a high pulsed output power of more than 100MW. With the modulator system, new drilling concepts for cost efficient drilling of very deep holes required for enabling a broad application of geothermal energy for base load energy provision are investigated. Besides the development of the basic modulator concept, the Ph.D. position involves also the detailed modelling and optimisation of the modulator system. For verifying the concept and the models, laboratory scale test systems are built and operated in our medium voltage laboratory. After a successful test, a full-scale prototype system should be built in collaboration with industry partners and other research institutes.

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23. PhD in sustainable catalysis

Summary of Doctoral Project:

The project explores the development of highly active and selective, heterogeneous catalysts with attention to catalyst synthesis and characterization and mechanistic aspects. The ultimate goal of the project is the establishment of guiding principles to design novel catalyst formulations with the potential to replace existing industrial catalysts that are either toxic or rely on a comparatively high loading of noble metals.

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24. PhD & Postdoc Positions for Synthetic Biology-Inspired Therapies

Summary of Doctoral Project:

The projects will combine basic and translational research to develop novel synthetic biology-inspired principles. Rational programming the behavior of human cells will shape future biomedical applications. This may include the design of novel biosensors, gene switches and genetic closed-loop circuits, the synthesis of novel chemical structures to interface and actuate cellular activities or to design programmable cellular implantable devices. Our group uses state-of-the-art Synthetic Biology principles to engineer human cells and develop cell-based therapies for the treatment of cancer as well as metabolic, neurodegenerative, autoimmune and infectious diseases. Please consult our webpage and published work for further information.

Last Application Date: Open until filled

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25. PhD position: material failure prediction with physics-induced machine learning

Summary of Doctoral Project:

The PhD position will focus on the development of a physics-induced (graph) neural network framework applied to the prediction of the failure of complex materials with specific micro-mechanical structures. Prediction of material failure is a complex problem because it is largely affected by disorder in the microstructure. While the average material performance of a given microstructure is well described by homogenization techniques, the exact prediction for a specific material element is extremely challenging. The objective of this project is to develop a physics-induced machine learning approach based on (graph) neural networks and reinforcement learning algorithms to predict the overall strength of a given piece of material. The candidate will be responsible for the development of machine learning framework, its implementation, and validation with data from numerical simulations.

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26. PhD Position: Personalized Control for Safety-Critical Biomedical Systems

Summary of Doctoral Project:

As data-driven methodologies prove their potential in countless applications, their application in control remains limited, which is particularly true for safety-critical applications in biomedical engineering. This project will investigate the feasibility of advanced and data-driven control in this domain, aiming to enable reliable control solutions that can automatically adapt to each patient’s need. The starting point of the project is the investigation of these questions in the context of cardiac assist devices with the goal of developing an adaptive physiologic controller for a heart pump. Available physiologic controllers and state-of-the-art heart pumps serve as a basis and the developed advanced control techniques can be implemented on available testing facilities. This ensures the direct connection to real-world (control) challenges and opportunities, which will be identified in direct exchange with medical experts in the field.

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27. Doctoral student in ecosystem gas exchange and nitrogen dynamics

Summary of Doctoral Project:

The doctoral project is part of the interdisciplinary project Understanding drivers and origins of N2O fluxes in agroecosystems (DONA) carried out with colleagues from Agroscope and Empa in Switzerland. The project aims at understanding drivers and origins of nitrous oxide losses to the atmosphere, besides nitrate leaching, in order to identify the best N management option(s) for climate-smart agriculture at a long-term flux measurement site (cropland) and on existing arable field trials

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28. Doctoral Position in Earth Observation and Remote Sensing

Summary of Doctoral Project:

The research focuses on investigating/developing generic methods and algorithms in the context of multi-modal synthetic aperture radar (SAR) for the estimation of environmental parameter over arctic regions. SAR is an active remote sensing technique for estimating a variety of surface features, as e.g. topographic heights, displacements, quantitative bio-physical parameters and has found applications in several domains of the artic region, as e.g. the monitoring of infrastructure and permafrost-related subsidence’s. Among the most rapid and dramatic changes in the artic regions are retrogressive thaw slumps. These slumps have major impacts by changing ecosystem and hydrological equilibria and furthermore impact the earth system on a global scale by reinforcing climate change with the additional mobilization of organic carbon that was previously stored in the frozen soil. Due to the remote landscape, only space-born approaches are feasible to monitor them.

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