ETH Zurich, Switzerland invites online Application for number of Fully Funded PhD Degree at various Departments. We are providing a list of Fully Funded PhD Programs available at ETH Zurich, Switzerland.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: PhD Position: SNSF Sinergia Research Project «Family Custody Arrangements and Child Well-Being in Switzerland» – Sub-project Housing, Architecture, and Mobility
The overall project focuses on post-separation custody arrangements and their impact on children and will contribute to the identification of risk and resilience factors for child well-being after parental union dissolution in Switzerland. Building on the insights of social demography, psychology, architecture and housing studies, and law, this interdisciplinary project investigates the interdependent effects of four key dimensions on child well-being: socio-structural (social inequalities within and between families), relational (interpersonal relationships between family members), spatial (housing-mobility arrangements), and legal (legal regulations and court decisions). The position is placed under the responsibility of Prof. Dr Elli Mosayebi, Professor for Architecture and Design, Department of Architecture, ETH Zurich. You will specifically work on the architecture and housing study, co-supervised by Prof. Dr Joëlle Darwiche, University of Lausanne. In addition, you will benefit from being associated with the Doctoral Programme at the ETH Zurich Department of Architecture’s Institute of Landscape and Urban Studies (LUS). ETH Wohnforum – ETH CASE (Centre for Research on Architecture, Society & the Built Environment) is an interdisciplinary institute for research, consulting and education in the field of housing, architecture, and urban development at the department of architecture at ETH Zurich.
Deadline : Open until filled
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD student positions in nutritional breath metabolomics
Food intolerances are a major cause of functional gastrointestinal disorders, and while they can be managed by dietary intervention, correct diagnosis is essential for effective treatment. This interdisciplinary project will investigate the molecular composition of human exhaled breath as a potential source of biomarkers reporting on the clinical traits associated with lactose malabsorption (LM) (Lactobreath profiles) as a proof-of-concept for future application of this technology in the diagnosis of food intolerance. The identified breath biomarkers will be investigated in relation to lactose malabsorption symptoms, usual diet, and clinical traits associated with lactose malabsorption, including genetic polymorphisms regulating the expression of the lactase gene, breath hydrogen, and lactose-derived urinary metabolites. Lactobreath profiles will be mechanistically linked with metabolic traits associated with lactose malabsorption, including colonic gases and urine metabolome.
Deadline : Open until filled
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD in Multiscale response of skin to mechanical stressors
This project is part of a collaborative and interdisciplinary effort involving researchers in cell biology, skin mechanics, and biomaterials to bring new understanding of tissue-level response to mechanical stressors, and translate this to clinical applications. The doctoral student in the Tibbitt group will focus on the fabrication, characterization, and implementation of 3D biomaterials that represent a physiologically- and mechanically-relevant models of dermal skin tissue, and their integration in bioreactors, as well as characterization of the biological response. The goal is to have 3D in vitro system to mimic the ex vivo conditions and to control each of the physical state variables of the cell microenvironment in vitro. You are expected to work in close collaboration with the Mazza group (D-MAVT, ETHZ) and Werner group, D-BIOL, ETHZ). In addition, you are expected to contribute to lab duties, and will have the opportunity to contribute to teaching within the group (Student supervision and Lab workshops for MSc students of D-MAVT).
Deadline : Open until filled
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD position in Geobiology and Microbiology of Extreme Environments
The PhD project will investigate how seismic activity and oxidative stress affect subsurface microbial and viral communities. For this position you have a strong background in either geobiology, environmental microbiology and/or computational biology (or related subjects) and are interested in microbial evolution and extreme environments. This project includes experimental and computational components including microbial enrichment experiments, underground field experiments at the Bedretto Underground Lab’s Deep Life Observatory and metagenomic/metatranscriptomic/metaproteomic analysis.
Deadline : Open until filled
(05) PhD Degree – Fully Funded
PhD position summary/title: PhD in device engineering for efficient microhistology
Microtissues, including organoids and spheroids, are transforming biological research, drug discovery, and personalized medicine. Histological analysis of microtissues currently allows us to decipher disease mechanisms and identify potential therapeutic molecules for cancer patients. However, the histology of these models remains highly inefficient, wasteful, time intensive, and costly as it is difficult to position heterogeneous and complex microtissues for efficient processing. This project aims to address this limitation by the use of acoustofluidics for positioning microtissues within a gel embedding medium. We will develop a device to carry out the positioning of the microtissues as well as an associated labware needed to streamline the process and integrate it within existing histology workflows. Microtissue processing is highly relevant in basic and applied research and patient care, especially considering the need for personalized therapies in disease treatment. Improving histological analyses will have a positive impact on novel discoveries of disease mechanisms and effective drug molecules.
Deadline : Open until filled
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(06) PhD Degree – Fully Funded
PhD position summary/title: PhD position “Re-engineering informal construction through circular practices and models”
This PhD position on circular practices in informal construction is at the Chair of Circular Engineering for Architecture (CEA) at ETH Zurich, Switzerland, and will be conducted in coordination with the Housing unit (School of Built Environment and Development Studies), at the University of KwaZulu-Natal, South Africa. We are seeking a highly motivated and qualified PhD researcher to join our team working on developing material passports for low-income economies in the context of re-engineering informal construction through circular practices and models. You will be responsible for conducting research and developing methodologies for the creation and implementation of material passports in South African vulnerable communities.
Deadline : Open until filled
(07) PhD Degree – Fully Funded
PhD position summary/title: PhD and Post-Doctoral Positions on the Application of Large Language Models in Marketing
The focus of the positions is on research, aiming at publications in leading international journals. Research can build to the chair’s extensive track record in the field of Data Science and Chatbots, but we are also open to related topics. The PhD position involves assisting the chair with administrative tasks and in teaching, while the PostDoc position involves teaching one course per year (e.g., electives for master students and/or PhD courses, where one course is 90 minutes of teaching/week in English).
Deadline : Open until filled
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD candidate for developing new concepts for automatically detecting de-energized overhead lines
We are looking for outstanding, highly motivated people interested in pursuing PhD research on new concepts for automatically detecting if overhead lines for electric locomotives or trucks are energized. In railway grids with a high level of electrification for reducing CO2 emission, there are always also areas without electrification, e.g. for shunting/loading. For operating locomotives in both areas, the pantograph connecting the locomotive to the overhead line must be operated properly at transition points between energized and de-energized areas to avoid costly damage to the pantograph/overhead line and the related outages of locomotives. With your PhD project, you should develop an automatic detection system of the transition points between energized/de-energized overhead lines to avoid damaging the pantograph/overhead line. Such detection systems and based on it an automatic operation of the pantograph are mandatory for future automatic driving systems of locomotives. So far, no concepts for such detection systems have been investigated, thus the project will open a new research area. The system for automatically detecting the transition points should be based on the measurement of the E-field in front of the locomotive. As an energized overhead line generates a high E-field between the overhead line and the rail and a de-energized overhead line does not, detecting the end of the electrification is based on the measurement of a changing/decreasing E- field in front of the locomotive. Since the pantograph operation is relatively slow and the detection must happen while the locomotive is driving, the transition point must be detected some tens of meters in front of the locomotive. Therefore, the E-field changes, which must be detected, are relatively small, which makes a failsafe detection of a transition point challenging.
Deadline : Open until filled
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(09) PhD Degree – Fully Funded
PhD position summary/title: PhD position in emerging black soldier fly biowaste processing
You are expected to explore heterogeneous and dynamic rearing conditions resulting in the optimization of higher-value products, for example, melanin, chitin or lauric acid. The objective is to develop a dynamic growth model that predicts rearing conditions for optimal waste treatment and production of high-value products. Ultimately, the findings are expected to increase the understanding of this novel process and aid the development of practical tools. The research will be completed within the collaboration on black soldier fly research by ETH Zurich, Eawag and the Singapore-ETH Centre. The project background should be seen as a broad framework that can be detailed and altered based on the applicant’s background and interest. As a Doctoral Candidate, you will be responsible for research working towards the development of a dynamic growth model to predict rearing conditions for waste treatment and the production of high-value products.
Deadline : Open until filled
(10) PhD Degree – Fully Funded
PhD position summary/title: PhD in role of biogenic macromolecules for ice nucleation of fertile soils
Ice-nucleating particles (INPs) represent only a tiny fraction of the atmospheric aerosol, but they are key actors in cloud processes including precipitation formation, as they initiate the ice phase in clouds. Although mineral dusts are probably the most important and best established type of atmospheric INPs, there are still major unknowns that preclude a reliable prediction of ice crystals forming on them. Different factors have been identified that influence their freezing temperatures. Apart from the mineral type, these are particle size, interactions with solutes and water, adsorption of organic molecules, and freezing mode. Yet, some of these factors do not seem to matter in general, but only for some mineral types. Therefore, attempts to generalize them to all types of mineral INPs produce conflicting results. Our group has longstanding experience in the investigation of atmospheric INPs and a history of developing cloud chambers and cold-stage experiments, among them the microfluidic device MINCZ, the drop freezing assay DRINCZ and the continuous flow diffusion chamber HINC. Moreover, a broad range of analytical techniques for aerosol characterization are available in our group and at ETH Zurich.
Deadline : Open until filled
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(11) PhD Degree – Fully Funded
PhD position summary/title: Fully funded PhD in role of particle size and mixing state for ice nucleation on mineral dust
Ice-nucleating particles (INPs) represent only a tiny fraction of the atmospheric aerosol, but they are key actors in cloud processes including precipitation formation, as they initiate the ice phase in clouds. Although mineral dusts are probably the most important and best established type of atmospheric INPs, there are still major unknowns that preclude a reliable prediction of ice crystals forming on them. Different factors have been identified that influence their freezing temperatures. Apart from the mineral type, these are particle size, interactions with solutes and water, adsorption of organic molecules, and freezing mode. Yet, some of these factors do not seem to matter in general, but only for some mineral types. Therefore, attempts to generalize them to all types of mineral INPs produce conflicting results. Our group has longstanding experience in the investigation of atmospheric INPs and a history of developing cloud chambers and cold-stage experiments, among them the microfluidic device MINCZ, the drop freezing assay DRINCZ and the continuous flow diffusion chamber HINC. Moreover, a broad range of analytical techniques for aerosol characterization are available in our group and at ETH Zurich.
Deadline : Open until filled
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(12) PhD Degree – Fully Funded
PhD position summary/title: PhD position in Differentiable Simulation and Machine Learning for Musculoskeletal Robotics
This doctoral position will focus mainly on the simulation and computational aspects, while most hardware components are fabricated and built by colleagues in the Soft Robotics Laboratory. Simulation to reality validation needs to be performed through experimental setups that the candidate should be able to design and use. A strong interest in working hands-on with robotic systems and validating simulations in the real world on robots is desirable. As a PhD student, you will develop and publish on new software frameworks and their physical validation. You will regularly present your work at international robotics and machine learning conferences. Your responsibilities will also include supervising bachelor and master students in their thesis works, supporting the Soft Robotics Laboratory in teaching its graduate classes, and in preparing grant proposals.
Deadline : Open until filled
(13) PhD Degree – Fully Funded
PhD position summary/title: PhD Position in data-driven characterisation of paediatric sepsis
Sepsis is a leading cause of mortality in children worldwide. A major limitation in pediatric sepsis management is the delay in obtaining accurate diagnosis because children with sepsis initially often have symptoms akin to common and mild viral illnesses. Rapid and reliable diagnosis of sepsis is a major unmet clinical need, which will be addressed in the proposed project. The goal of this large and innovative project is to improve the diagnosis of pediatric sepsis by assessing the host response using so-called “omics”. Specifically, we will measure the host response at protein (proteomics) and metabolic (metabolomics) level, in addition to the gene expression (transcriptomics). Thereby, we hope to identify novel markers which can improve the diagnosis and management of sepsis in children. Using machine learning on this unique dataset, we aim to characterize the individual response to sepsis. Thereby we hope to identify new avenues for better, more personalized sepsis management.
Deadline : Open until filled
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD position in Machine Learning Directed Design of Actuators from Biological Muscle
You will join the efforts of a SNF Sinergia consortium focused on Machine-learned Design and Bioxolography of Functional 3D Skeletal Muscle Tissues. The consortium consists of 4 research groups within Switzerland and Germany, with expertise in cell biology, muscle tissue engineering, and volumetric 3D printing techniques. Our group’s expertise fits in on the computational modeling and tissue and mechanical engineering aspects of the project. As such, the research will be inherently collaborative and interdisciplinary. Your role will be mostly computational, but will also involve some amount of biofabrication and work in the laboratory. Aside from the Sinergia consortium, you will also support the efforts of the ALIVE Initiative of ETH Zürich which aims to elucidate and apply the design principles of living systems as a basis for sustainable, intelligent, and resilient materials and technologies of the future. Our approach encompasses studying natural systems and developing biohybrid or biomimetic synthetic systems bridging across scales, from the nano to the macro and structural scale. The Soft Robotics Lab is an integral part of the ALIVE Biohybrid Project Stream.
Deadline : Open until filled
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD position in the Distributed Computing Group
In our group we try to apply and unite the approaches and techniques of theory and practice. Some members of our group focus on algorithms and mathematical proofs, some on system design and building. As a new member of the group, you are supposed to contribute to research activities in the group and gradually build your own independent research profile according to your interests. You are expected to work towards a doctoral degree, and participate in the teaching activities of the group.
Deadline : Open until filled
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD Position: Computer Simulation of Spinal Segment Mechanics
The available position is funded under the EU H2020 program “METASTRA”. METASTRA aims to improve the prevention of fractures in patients with vertebral metastases, and to deliver patient-targeted treatment by developing robust computational models that will reliably stratify patients based on their fracture risk. METASTRA will provide a combination of validated biomechanical models and data driven AI models that will be incorporated in a Decision Support System (DSS). You will gain the necessary interdisciplinary skills demanded by industry and academia to deliver timely and cost-effective solutions to one of the most challenging problems in spinal healthcare.
Deadline : Open until filled
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(17) PhD Degree – Fully Funded
PhD position summary/title: PhD position in XR applications for inspection of net-zero carbon infrastructure
The project will be carried out by an XR Team: a postdoc, a doctoral student and an XR technical expert over four years. The XR Team is responsible for conducting cutting-edge research and developing methods and tools with the goal of delivering a flexible plug-and-play toolbox that can be applied in three exemplary projects for inspection, assembly (including dis- and re-assembly), and operations. The toolbox should be developed as an extensible XR platform such that other researchers within the AEC and ETH community can adopt it to create their own XR pipelines. The aim is not only to push the research in XR technology but also to lower the barrier of entry, democratizing the use of XR in AEC and further extending the impact of this lighthouse project. Being domain- and material-agnostic, the XR team will provide unique leverage to the large body of ongoing research in sustainable construction, across disciplines, specializations, materials, and structural systems.
Deadline : Open until filled
(18) PhD Degree – Fully Funded
PhD position summary/title: PhD position in forestry and remote sensing: Tree species monitoring
Forests provide numerous ecological, economic, and climatic benefits, yet they are highly vulnerable to climatic extremes. Actively managing forest ecosystems for resilience and adaptation is crucial to ensure that forests continue providing these benefits. Forest monitoring – in particular tree species identification – is essential for assessing biodiversity, understanding forest resilience to climate change, and developing forest management strategies. You will work in a multidisciplinary project combining aerial imagery, ground-truth data and terrestrial lidar data from Swiss-, European, and Global forests, using deep learning methods to identify the best ways forward for a first of its kind automatic tree species detection model.
Deadline : Open until filled
(19) PhD Degree – Fully Funded
PhD position summary/title: PhD student in Virtual Reality and Brain-Computer Interfaces
The aim of this project is to develop intelligent and interactive software experiences that detect physiological reactions related to cybersickness/simulator sickness, breaks in presence, and embodiment. We will develop sensing models and signal processing algorithms for the early detection of these reactions. These will be input to our optimization-based engine for real-time system and UI adaptation.The work will focus on the identification, characterization, and real-time detection of neurophysiological markers associated with users’ mental states. A second component of the work will focus on the real-time adaptation of the immersive environment. The work will comprise methodological and theoretical aspects. First, we will investigate the state of the art of the various dimensions associated with “user experience” in VR, the factors that influence their perception, and a range of “offline” markers that have been highlighted in prior work. From this, we will define experimental protocols for controlled empirical studies that we will conduct with state-of-the-art EEG headsets in immersive settings, where we will electroencephalographic data associated with the different mental states of VR users. Through an in-depth analysis, we will determine the individual neuromarkers that relate to the various dimensions of user experience, with a particular focus on the perception of presence, embodiment, and cyber sickness. For this data analysis, we will use and further develop signal processing techniques, including statistical methods as well as novel learning-based approaches. These include specific methods, based for example on Riemannian geometry tools. We aim at developing novel objective metrics that are capable of evaluating the evolution of feelings related to embodiment, presence, and sickness in real time. We will compare our objective methods’ success with the current default evaluation, which is mainly based on subjective questionnaires or averaged experimental data.
Deadline : Open until filled
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(20) PhD Degree – Fully Funded
PhD position summary/title: PhD position in Cell Biology and Genetic Immunity
Living cells may contain extra-chromosomal DNA circles excised from chromosomes or of exogenous origin, such as when we transfect them with plasmid DNA. Remarkably, interphase nuclei of mammalian cells are able to evict this extra-chromosomal DNA (interphase and mitotic sorting). This observation suggests that mammalian nuclei are able to specifically distinguish extra-chromosomal from chromosomal DNA and to mount a dedicated response that confines it away from its genome. We postulate that this process contributes to genome defence by preventing both the expression of exogenous DNA and its integration in the genome. How cells achieve this is unknown and shall thus be elucidated in the PhD project. In this project, a mechanism(s) by which transfected plasmid DNA is evicted from the interphase nuclei of human cell lines shall be dissected. By employing a loss-of-function approach using CRISPRi (repressing specifically the expression of candidate genes) hit genes will be identified microscopically and subsequently probed for their role in plasmid eviction from the nucleus. This work will thereby identify essential players involved in the nuclear eviction of plasmid DNA to shed light on the mode and efficiency of an understudied system of genome defence in mammalian nuclei.
Deadline : Open until filled
(21) PhD Degree – Fully Funded
PhD position summary/title: PhD student in Solar Orbiter Science
You will undergo original research in the area of solar wind formation. The project is dominantly data analysis and you will actively engage with international instruments and mission consortia. The project will entail analysing data not only from the Solar Orbiter mission but also from Hinode, IRIS, SDO and potentially DKIST. The analysis software is based both in Python and IDL. As part of your role as a PhD student, you will also actively engage in the teaching of the D-PHYS department at ETH.
Deadline : Open until filled
(22) PhD Degree – Fully Funded
PhD position summary/title: PhD Position in Imaging Sensor Optimization, Control and Image Reconstruction
The PhD position involves researching and developing sensor control strategies, sensor simulation, and optimization of acquisition parameters for various sensor technologies. You will also work on advanced image reconstruction techniques and their applications. In close collaboration with researchers and engineers, you help to enable practical applications of imaging sensor optimization. Additionally, you will contribute to the preparation and publication of research papers in high-impact journals and conference processing as well as to patent invention reports.
Deadline : Open until filled
About ETH Zurich, Switzerland- Official Website
ETH Zürich is a public research university in the city of Zürich, Switzerland. Founded by the Swiss Federal Government in 1854 with the stated mission to educate engineers and scientists, the school focuses exclusively on science, technology, engineering and mathematics. Like its sister institution EPFL, it is part of the Swiss Federal Institutes of Technology Domain, part of the Swiss Federal Department of Economic Affairs, Education and Research.
In the 2021 edition of QS World University Rankings, ETH Zurich was ranked 6th in the world, placing it as the second-best European university after the University of Oxford. In the 2020 QS World University Rankings by subject, it ranked 4th in the world for engineering and technology (2nd in Europe) and 1st for earth & marine science. Also, ETH was rated 8th in the world in the Times Higher Education World University Rankings of 2020.
The university is an attractive destination for international students thanks to low tuition fees of 809 CHF per semester, PhD and graduate salaries that are amongst the world’s highest, and a world-class reputation in academia and industry. There are currently 22,200 students from over 120 countries, of which 4,180 are pursuing doctoral degrees.
As of November 2019, 21 Nobel laureates, 2 Fields Medalists, 2 Pritzker Prize winners, and 1 Turing Award winner have been affiliated with the Institute, including Albert Einstein. Other notable alumni include John von Neumann and Santiago Calatrava. It is a founding member of the IDEA League and the International Alliance of Research Universities (IARU) and a member of the CESAER network.
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