eth master thesis math

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Department of Materials

Master thesis.

The Master’s thesis concludes the Master’s degree programme. It constitutes a six-month, full-time project aimed at advancing the skills and capabilities of students to work independently and creatively toward the solution of a research problem.

Students are asked to register on myStudies for the Master's thesis and submit the  Download registration form (PDF, 868 KB) vertical_align_bottom  to the D-MATL Study Administration before starting to work on the thesis.

The Master's thesis generally takes place during the entire 4th semester of the Master’s degree programme and is conducted under the supervision of a D-MATL research group or an associated professor . During those six months the students are supported by doctoral students and other researchers of the respective research group. In specific cases it is possible to do the Master's thesis in another department of ETH or at another university.

The Master's thesis is concluded with a report and oral presentation that are graded by the supervisor. Please submit a copy of the report as a PDF to the D-MATL study administration.

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3 Format of the Master and Bachelor Theses

3.1 – language.

The Master thesis has to be written in English and Bachelor thesis in English or German, comprehensibly and in an appropriate style. It is recommended to have the thesis corrected by a third person before handing it in.

3.2 – Formal Layout

If the research group, in which the thesis project is carried out, does not have formal guidelines for the layout of the thesis, the following are recommended:

Format: A4 Page margins: top and bottom: 3 cm, left 3 cm, right 2 cm Font & Font size: 11-12 points, Arial recommended Columns: single-column Paragraph: line spacing 1.5, justified Page numbers: bottom, starting from introduction Paper quality: minimum 80 g/m2 paper

There may be additional (partially discipline specific) guidelines for figures and reference formats. Ask your supervisor.

3.3 – Number of Pages

The number of pages is no criterion for the quality of a bachelor or master thesis. The content and the engagement with the subject are the key factors (quality is more important than quantity; a typical range is 20-30 pages for the Bachelor thesis and 30-50 pages for the Master thesis).

3.4 – Paper Form

It is possible to write the master thesis directly in the form of a scientific paper. This possibility will be discussed and agreed with the Examiner as early as possible ( see section 2.6 Affiliation with Publications ). In this case, the formal requirements of the corresponding journal apply (e.g. layout, number of pages). It is even more important in this situation that the contribution of the student is traceable for grading purposes.

Guidelines for Scientific Communication: Guidelines for Scientific Communication - Copyright © 2017 by Institute of Food, Nutrition and Health, ETH Zurich. All Rights Reserved.

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Computational Science and Engineering

 REMEMBER: each project for a Term, BSc-, or MSc-Thesis must be approved via this form .

A thesis project is usually supervised and graded by a lecturer in charge of teaching a Core Course or a course in a Field of Specialization, but any other lecturer of ETH Zurich, who is entitled to supervise master thesis in her or his own department is also eligible.  

The topic of a thesis project must be approved by the Director of Studies CSE. Approval can be requested via the form above and needs a brief description of the project. That description must convey that the following requirements are satisfied:

All projects in CSE must involve the application of core CSE techniques and must have a strong software implementation component. Algorithm development and implementation, numerical or discrete modeling, or simulations must constitute the main contribution of the student to the project.

If a thesis project is conducted at an institution or company outside ETH Zurich, an authorized lecturer of ETH Zurich must take responsibility as in-​house supervisor.  

Please also note the gen­eral pro­ced­ures for do­ing thesis pro­jects:

protected page Procedure for Semester/BSc/MSc-theses lock

All theses/projects end with a written report (including the declaration of originality) and with a presentation.

The Bachelor Thesis in CSE ends the BSc program and can be written not earlier than 5th semester, better in 6. semester of study. It should require about 420 hours and 14 ECTS are obtained. Both full time and part time work are allowed.

A Term Thesis in CSE should be computational and application oriented work in a team in order to deepen the knowledge in an application area. It should require about 160-240 hours and 8 ECTS are obtained for an accepted paper. The supervisor defines the tasks to be accomplished and establishes the dates of start and end of the work. A term theis is graded pass/fail. The Master Thesis takes 6 months, which is a strict deadline for its completion, and is supposed to be full-​time work. It concludes the CSE Master studies and should train students for independent work on a particular topic. 30 ECTS credits are awarded for an accepted thesis.

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ETH for Development  

Ba and ma thesis topics.

ETH4D lists BA and MA thesis topics across ETH Zurich that are related to global development. If you are interested, please get in touch with the listed supervisor directly.

Opportunities published by ETH members on SiROP

ETH Zurich uses SiROP to publish and search scientific projects. For more information visit sirop.org call_made .

Unravelling the spatial and biomechanical dynamic of fracture healing in mice

Fracture healing is a complex process that involves inflammation, angiogenesis, and bone remodeling. The remodelling process helps maintain bone density, repair micro-damage that occurs due to everyday activities, and adapt bones to the specific needs of an individual's body. Mechanical loading is a crucial factor in the regulation of fracture healing. The forces and strains experienced by the bone during everyday activities influence the cellular responses, callus formation, bone deposition, remodelling, and, ultimately, the successful recovery of the fractured bone. The mechanisms underlying spatial cell reorganization during loading, which contributes to fracture healing, remain unclear. The project aims to investigate and explore the fracture healing process of mice using spatial transcriptome changes in response to mechanical loading. By shedding light on this aspect, the project aims to contribute to the broader understanding of fracture healing and potentially pave the way for more effective treatment strategies in the future. Show details add remove

Spatial transcriptomics, Dimensionality reduction, Spatial expression pattern, Spatial interaction, Cell Segmentation and Visualization, Fracture healing, Bone

IDEA League Student Grant (IDL) , Semester Project , Course Project , Internship , Bachelor Thesis , Master Thesis , ETH for Development (ETH4D) (ETHZ) , ETH Zurich (ETHZ)

Description

Contact details, more information.

Open this project...  call_made

Published since: 2024-03-07 , Earliest start: 2024-03-07 , Latest end: 2024-08-01

Organization Müller Group / Laboratory for Bone Biomechanics

Hosts Singh Amit

Topics Medical and Health Sciences , Mathematical Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Biology , Physics

Pasteurizer development for biogas-powered effluent treatment

Anaerobic digestion (AD) is considered one of the oldest and most sustainable biological treatment technologies for stabilizing and reducing organic waste, including food waste, sewage sludge, industrial waste, and farm waste. AD transforms organic matter into biogas (60–70 vol-% of methane), thereby reducing the volume of the waste whilst destroying some of the pathogens present in the waste feedstocks and limiting odor problems associated with waste materials (Appels et al., 2008; Gerardi, 2003). AD is a promising energy, waste management, and sanitation solution in low-resource, low-income settings (Forbis-Stokes et al., 2016; Owamah et al., 2014). However, it does not fully eliminate pathogens for safe environmental discharge. Three ETH master students (Hardeman, 2022; Jäggi, 2023; Luz, 2022) iteratively developed and optimized the biogas reactor and the solution for sludge pasteurization to homogeneously heat the effluent and render the liquid safe for discharge. However, the technology needs further improvements and adaptations to operate reliably in continuous mode in all environmental conditions. Show details add remove

thermodynamics, mechanical design, manufacturing, measurements

Master Thesis , ETH for Development (ETH4D) (ETHZ) , ETH Zurich (ETHZ)

Published since: 2024-02-02 , Earliest start: 2024-02-01 , Latest end: 2024-11-30

Applications limited to ETH Zurich , Department of Mechanical and Process Engineering

Organization Global Health Engineering

Hosts Tkaczuk Jakub

Topics Engineering and Technology

Analysis and treatment of wastewater from plastic recycling in Blantyre, Malawi

Monitoring and treatment of plastic washing wastewater from recycling processes is often overlooked, though the high pH, chemical oxygen demand, suspended solids, and oil and grease concentrations can be problematic (Ozdemir and Yel 2023). Treatment of wastewater from plastic recycling is critical to both public and environmental health, since solid waste, sanitation, and water are inextricably linked (Narayan et al. 2021). This thesis project will contribute to a closed-loop plastic recycling pilot for HDPE bottles in Blantyre, Malawi. Show details add remove

wastewater, plastic recycling, resource conservation, low-income setting

Published since: 2024-01-12 , Earliest start: 2024-02-01 , Latest end: 2024-09-30

Applications limited to ETH Zurich

Optimizing Membrane Technology for Water Filtration in Low and Middle-Income Settings

Openversum is dedicated to pioneering sustainable, cost-effective water filtration solutions for communities in low and middle-income regions. Our advancements in membrane technology represent a significant leap forward. However, continuous innovation is essential to optimize these membranes for local environmental conditions and budgetary constraints. Striking a balance between affordability, efficiency, and local adaptability is crucial for the widespread adoption of this technology. Show details add remove

Membrane Science, Water Filtration, Low-Cost Production, Material Science, Polymer Chemistry, Industrial Upscaling, Sustainable Technology, Environmental Engineering, Water Purification

Master Thesis , ETH for Development (ETH4D) (ETHZ)

Published since: 2023-12-21 , Earliest start: 2024-01-07 , Latest end: 2024-09-30

Applications limited to Department of Mechanical and Process Engineering

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ETH AI Center  

Semester and thesis projects.

The ETH AI Center offers a wide range of semester and thesis projects for students at ETH Zurich, as well as other universities. Please see the list below for projects that are currently available.

Are you a student? Check out our Semester and Thesis projects below!

ETH Zurich uses SiROP to publish and search scientific projects. For more information visit sirop.org call_made .

Lifelike Agility on ANYmal by Learning from Animals

The remarkable agility of animals, characterized by their rapid, fluid movements and precise interaction with their environment, serves as an inspiration for advancements in legged robotics. Recent progress in the field has underscored the potential of learning-based methods for robot control. These methods streamline the development process by optimizing control mechanisms directly from sensory inputs to actuator outputs, often employing deep reinforcement learning (RL) algorithms. By training in simulated environments, these algorithms can develop locomotion skills that are subsequently transferred to physical robots. Although this approach has led to significant achievements in achieving robust locomotion, mimicking the wide range of agile capabilities observed in animals remains a significant challenge. Traditionally, manually crafted controllers have succeeded in replicating complex behaviors, but their development is labor-intensive and demands a high level of expertise in each specific skill. Reinforcement learning offers a promising alternative by potentially reducing the manual labor involved in controller development. However, crafting learning objectives that lead to the desired behaviors in robots also requires considerable expertise, specific to each skill. Show details add remove

learning from demonstrations, imitation learning, reinforcement learning

Master Thesis

Description

Contact details, more information.

Open this project...  call_made

Published since: 2024-03-25

Organization ETH Competence Center - ETH AI Center

Hosts Li Chenhao , Li Chenhao , Klemm Victor

Topics Information, Computing and Communication Sciences

Learning Real-time Human Motion Tracking on a Humanoid Robot

Humanoid robots, designed to mimic the structure and behavior of humans, have seen significant advancements in kinematics, dynamics, and control systems. Teleoperation of humanoid robots involves complex control strategies to manage bipedal locomotion, balance, and interaction with environments. Research in this area has focused on developing robots that can perform tasks in environments designed for humans, from simple object manipulation to navigating complex terrains. Reinforcement learning has emerged as a powerful method for enabling robots to learn from interactions with their environment, improving their performance over time without explicit programming for every possible scenario. In the context of humanoid robotics and teleoperation, RL can be used to optimize control policies, adapt to new tasks, and improve the efficiency and safety of human-robot interactions. Key challenges include the high dimensionality of the action space, the need for safe exploration, and the transfer of learned skills across different tasks and environments. Integrating human motion tracking with reinforcement learning on humanoid robots represents a cutting-edge area of research. This approach involves using human motion data as input to train RL models, enabling the robot to learn more natural and human-like movements. The goal is to develop systems that can not only replicate human actions in real-time but also adapt and improve their responses over time through learning. Challenges in this area include ensuring real-time performance, dealing with the variability of human motion, and maintaining stability and safety of the humanoid robot. Show details add remove

real-time, humanoid, reinforcement learning, representation learning

Hosts He Junzhe , Li Chenhao , Li Chenhao

Continuous Skill Learning with Fourier Latent Dynamics

In recent years, advancements in reinforcement learning have achieved remarkable success in teaching robots discrete motor skills. However, this process often involves intricate reward structuring and extensive hyperparameter adjustments for each new skill, making it a time-consuming and complex endeavor. This project proposes the development of a skill generator operating within a continuous latent space. This innovative approach contrasts with the discrete skill learning methods currently prevalent in the field. By leveraging a continuous latent space, the skill generator aims to produce a diverse range of skills without the need for individualized reward designs and hyperparameter configurations for each skill. This method not only simplifies the skill generation process but also promises to enhance the adaptability and efficiency of skill learning in robotics. Show details add remove

representation learning, periodic autoencoders, learning from demonstrations, policy modulating trajectory generators

Hosts Li Chenhao , Rudin Nikita

Topics Information, Computing and Communication Sciences , Engineering and Technology

Universal Humanoid Motion Representations for Expressive Learning-based Control

Recent advances in physically simulated humanoids have broadened their application spectrum, including animation, gaming, augmented and virtual reality (AR/VR), and robotics, showcasing significant enhancements in both performance and practicality. With the advent of motion capture (MoCap) technology and reinforcement learning (RL) techniques, these simulated humanoids are capable of replicating extensive human motion datasets, executing complex animations, and following intricate motion patterns using minimal sensor input. Nevertheless, generating such detailed and naturalistic motions requires meticulous motion data curation and the development of new physics-based policies from the ground up—a process that is not only labor-intensive but also fraught with challenges related to reward system design, dataset curation, and the learning algorithm, which can result in unnatural motions. To circumvent these challenges, researchers have explored the use of latent spaces or skill embeddings derived from pre-trained motion controllers, facilitating their application in hierarchical RL frameworks. This method involves training a low-level policy to generate a representation space from tasks like motion imitation or adversarial learning, which a high-level policy can then navigate to produce latent codes that represent specific motor actions. This approach promotes the reuse of learned motor skills and efficient action space sampling. However, the effectiveness of this strategy is often limited by the scope of the latent space, which is traditionally based on specialized and relatively narrow motion datasets, thus limiting the range of achievable behaviors. An alternative strategy involves employing a low-level controller as a motion imitator, using full-body kinematic motions as high-level control signals. This method is particularly prevalent in motion tracking applications, where supervised learning techniques are applied to paired input data, such as video and kinematic data. For generative tasks without paired data, RL becomes necessary, although kinematic motion presents challenges as a sampling space due to its high dimensionality and the absence of physical constraints. This necessitates the use of kinematic motion latent spaces for generative tasks and highlights the limitations of using purely kinematic signals for tasks requiring interaction with the environment or other agents, where understanding of interaction dynamics is crucial. We would like to extend the idea of creating a low-level controller as a motion imitator to full-body motions from real-time expressive kinematic targets. Show details add remove

representation learning, periodic autoencoders

Hosts Li Chenhao , Li Chenhao , Li Chenhao

Humanoid Locomotion Learning and Finetuning from Human Feedback

In the burgeoning field of deep reinforcement learning (RL), agents autonomously develop complex behaviors through a process of trial and error. Yet, the application of RL across various domains faces notable hurdles, particularly in devising appropriate reward functions. Traditional approaches often resort to sparse rewards for simplicity, though these prove inadequate for training efficient agents. Consequently, real-world applications may necessitate elaborate setups, such as employing accelerometers for door interaction detection, thermal imaging for action recognition, or motion capture systems for precise object tracking. Despite these advanced solutions, crafting an ideal reward function remains challenging due to the propensity of RL algorithms to exploit the reward system in unforeseen ways. Agents might fulfill objectives in unexpected manners, highlighting the complexity of encoding desired behaviors, like adherence to social norms, into a reward function. An alternative strategy, imitation learning, circumvents the intricacies of reward engineering by having the agent learn through the emulation of expert behavior. However, acquiring a sufficient number of high-quality demonstrations for this purpose is often impractically costly. Humans, in contrast, learn with remarkable autonomy, benefiting from intermittent guidance from educators who provide tailored feedback based on the learner's progress. This interactive learning model holds promise for artificial agents, offering a customized learning trajectory that mitigates reward exploitation without extensive reward function engineering. The challenge lies in ensuring the feedback process is both manageable for humans and rich enough to be effective. Despite its potential, the implementation of human-in-the-loop (HiL) RL remains limited in practice. Our research endeavors to significantly lessen the human labor involved in HiL learning, leveraging both unsupervised pre-training and preference-based learning to enhance agent development with minimal human intervention. Show details add remove

reinforcement learning from human feedback, preference learning

Hosts Li Chenhao , Li Chenhao , Chen Xin , Li Chenhao

Deep Learning and Data Collection in Speech Recognition for Individuals with Complex Congenital Disorders

Complex congenital disorders often result in speech and motor skill impairments, posing communication challenges. Existing non-English speech recognition tools struggle with non-standard speech patterns, compounded by a lack of large training datasets. This project aims to create a personalized framework for training German speech recognition models, catering to the unique needs of individuals with congenital disorders. You will learn to collect data and apply machine learning or deep learning models. Show details add remove

Machine Learning, Deep Learning, Speech recognition, Natural Language Processing, Speech Recognition

Published since: 2024-03-12

Hosts Vo Anh

Topics Information, Computing and Communication Sciences , Engineering and Technology , Behavioural and Cognitive Sciences

Towards AI Safety: Adversarial Attack & Defense on Neural Controllers

The project is collaborating between SRI and RSL/CRL lab and aims to investigate the weakness of the neural controller based on the state-of-the-art [3] attacking method. Show details add remove

Adversarial attack; safe AI; Reinforcement learning

Semester Project , Master Thesis

PLEASE LOG IN TO SEE DESCRIPTION

Published since: 2024-03-06 , Earliest start: 2024-03-06 , Latest end: 2024-09-30

Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne

Organization Robotic Systems Lab

Hosts Shi Fan , Shi Fan , Shi Fan

Learning Diverse Adversaries to Black-box Learning-based Controller for Quadruped Robots

The project aims to leverage the latest unsupervised skill discovery techniques to validate the state-of-the-art black-box learning-based controllers in diverse ways. Show details add remove

Diversity in RL, Trustworthy AI

Published since: 2024-03-02 , Earliest start: 2024-03-02 , Latest end: 2024-08-28

Applications limited to ETH Zurich , [nothing]

Towards interpretable learning pipeline: A visual-assisted workflow for locomotion learning

Current reinforcement learning (RL)-based locomotion controllers have shown promising performance. However we are still not clear about what is learned during the training process. In this project, we investigate the proper metrics and visualisation techniques to interactively steer the locomotion learning tasks. Show details add remove

Reinforcement learning; visualization; interpretable AI

Published since: 2024-02-28 , Earliest start: 2024-02-26 , Latest end: 2024-08-26

Hosts Zhang Xiaoyu , Shi Fan , Wang April , Shi Fan , Shi Fan

Topics Engineering and Technology

Misestimation of CT-perfusion output in acute stroke due to attenuation curve truncation

In this master's thesis project, we are looking for a candidate to apply machine learning techniques to correct and predict signals of incomplete CT perfusion imaging for ischemic stroke. We hope to use machine learning techniques to de-noise and correct for the truncation in CT perfusion signals. In particular, we aim to infer the true attenuation curve after the truncation time-point. Show details add remove

machine learning; CT perfusion imaging; ischemic stroke; contrast-media attenuation time-curves;

Published since: 2024-02-22 , Earliest start: 2024-06-01

Organization Bjoern Menze

Hosts Davoudi Neda , Yang Kaiyuan

Topics Medical and Health Sciences , Information, Computing and Communication Sciences

Continual Learning and Neural Networks’ Scaling Limit(s)

In this project, we aim to study the effect of the network’s architecture in continual learning, with a specific focus on the effect of scaling it to large width and depth, and their interplay with other architectural components such as residual connections. Show details add remove

continual learning, network scaling limits, kernels

Published since: 2023-12-05 , Earliest start: 2023-12-05

Hosts Lanzillotta Giulia

ETH Zürich CADMO Thesis Template

(Master) Thesis template v1.4 for CADMO (Center for Algorithms, Discrete Mathematics and Optimization) at the Swiss Federal Institute of Technology in Zurich (ETH Zürich).

Largely adapted from Adrian Nievergelt's template for the ADPS (lecture notes) project.

Have you checked our knowledge base ?

Message sent! Our team will review it and reply by email.

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Institute of Science, Technology and Policy

Master's thesis.

The Master’s thesis concludes the Master’s degree programme in Science, Technology and Policy. With the Master’s thesis, students demonstrate their ability to conduct scientific research based on the theoretical and methodological knowledge acquired during the MSc programme.

The thesis addresses a particular policy issue chosen by the student and does so in an interdisciplinary manner. Policy analysis plays a significant role in the research and the resulting thesis. Writing the Master’s thesis involves a full-time semester workload (six calendar months full-time, 30 ECTS). Because the thesis must be completed within six months, students are advised to refrain from taking additional courses and/or, as far as financially possible, from pursuing paid employment during this time.

Master's Thesis in short

On this page you can find a short overview of the features and requirements of the Master's thesis.

The complete regulation can be found in the documents below:

• Please check the Download Master's Thesis Guidelines (PDF, 228 KB) vertical_align_bottom .
• Please download the Master’s Thesis Download Assessment Form (PDF, 253 KB) vertical_align_bottom (fillable PDF document).

Students can commence work on the Master's thesis when both of the following conditions are met:

• They have completed their Bachelor's degree.
• They have acquired the number of ECTS points required for the Master's degree in all categories, with the except for credits for electives and the Master's thesis itself.  

The minimum number of credits required in each category is:

• Courses in social sciences: 27 credits
• Minor in natural sciences and engineering: 27 credits
• Case studies: 12 credits

The Master's thesis must be completed within 28 weeks. These 28 weeks include 26 weeks of work and 2 weeks for holidays, sick leave, and other brief absences.

Students are free to choose a start date in agreement with both supervisors. The start date is then registered in myStudies, subject to approval by the supervisor.

This binding deadline for each student is displayed on myStudies. If it is missed without notification, the Master's thesis will be graded as ' failed ' . The Director of Studies can extend the deadline under exceptional circumstances. The reasons must be stated in a written request by the student and the request must be approved by the Studies Director.

There is no required or maximum length. A rule of thumb is 40 - 50 pages, excluding appendices.

• Front-page layout

The front page must contain the following information:

• ETH and ISTP Logo.
• Thesis type (Master's thesis).
• Name of the student.
• Student ID number.
• Master’s degree programme in Science, Technology and Policy.
• Title of the Master's thesis.
• Supervisor and Co-Supervisor, with their academic title and institution.
• Date of submission (dd/mm/yyyy).
• Declaration of originality

Students must submit a signed declaration of originality when they submit their Master's thesis. Each copy needs to contain a Download declaration of originality (PDF, 183 KB) vertical_align_bottom .

If this student uses AI tools for language editing, this is acceptable but must be declared in the declaration of originality. Using AI tools for the substantive content of the thesis is not allowed.  

• Citation etiquette

All students are required to follow the guidelines Download 'Citation etiquette' (PDF, 67 KB) vertical_align_bottom .

Please also visit the webpage on plagiarism on the ETH student portal.

Please be aware that supervisors will normally run Master's theses through PlagScan or a similar platform to identify plagiarism problems before assessing the content of the thesis.

The Master's thesis should be supervised by two professors, who serve as supervisor and co-supervisor, respectively. One of these professors must be from the social sciences. The other professor should be from the natural or engineering sciences or the social sciences. The supervisor must be an ETH Zurich professor. She or he has the lead role in supervising and mentoring the student and grading the thesis. The co-supervisor can be from ETH or another academic institution. Subject to approval by the ISTP studies director, the co-supervisor (whether from within ETH Zurich or another academic institution) can also be a postdoctoral researcher or senior researcher/scientist with demonstrated experience in advising Master's and doctoral students. Such a co-advisor must be independent of the supervisor, i.e., she or he should not be a staff member of the supervisor.

Subject to approval by the supervisor and the ISTP studies director, the Master's thesis research can also be undertaken outside ETH Zurich under the co-supervision of a professor or postdoc/senior researcher at that institution (meeting the same conditions as for the co-supervisor within ETH Zurich, see above). In such cases, the supervisor (who must be an ETH Zurich professor) should assess the submitted Master's thesis independently of the ETH-external co-supervisor and provide a separate assessment and grading proposal. If both supervisor and co-supervisor are from within ETH Zurich, they may provide a jointly agreed assessment.

The supervisor and co-supervisor must, under any conditions, have full access to data and other material when assessing and grading the thesis, if necessary, under a non-disclosure agreement with the external institution. Research findings reported in a Master’s thesis must be replicable by third parties, normally by everyone in the respective scientific field and, in exceptional cases, at least by the supervisor and co-supervisor. Students are also responsible for determining where their research requires approval by the ETH Ethics Committee and, if applicable, secure approval with support from their supervisor.

According to a directive by the rector of ETH Zurich, research for the Master's thesis as such cannot be paid for. That is, paid work time (e.g., in the context of an internship or as a research assistant) cannot be used for work on the Master's thesis. Reimbursements (e.g., for travel costs, additional charges for food or accommodation) are permitted.

The supervisor and co-supervisor have the following duties:

• Define the theme of the Master's thesis in consultation with the student.
• Define the tasks in writing.
• Determine the date on which the student can begin the Master's thesis and the date on which the student can submit the thesis.
• Define the criteria for assessment of the Master's thesis.
• Assess and grade the thesis.
• Finding a topic, supervisors and preparation of the thesis proposal

Students are free to develop their own thesis topic or to select a topic suggested by a prospective supervisor and/or co-supervisor, and they are free to choose a supervisor and a co-supervisor whose interest aligns with a particular topic, subject to the above rules. The thesis must focus on a policy-relevant issue, and policy analysis should play a significant role in the research and resulting thesis. Once a topic is identified and agreed upon by both the student and the supervisor, the student will draft a thesis proposal of around 2 - 5 pages. This proposal must be approved by the supervisor before the research starts. The proposal should cover the following points:

• Supervisor and co-supervisor.
• Research question and its relevance.
• References and relevant scientific literature.
• Potential theoretical arguments addressing this question.
• Empirical research strategy and timeline.

On the following sites, you can find inspiration for potential thesis topics. 

• Student Theses Energy and Technology Policy Group  
• Abschlussarbeiten Institut für Raum- und Landschaftsentwicklung (D-BAUG) (German only)
• external page SiROP call_made
• Registration in myStudies

After the students and supervisors have agreed on a topic and a start date, students need to register for lecture number '860-0900-00 Master's Thesis' on myStudies .

The latest starting date can be 3 months after the end of the semester of registration.

To register the thesis in myStudies, students need to submit:

• Title of the thesis (the title can be changed later on).
• Start date.
• Names of the supervisors.
• Thesis proposal.

The duration of the Master's thesis is set to maximum 28 weeks (6 months plus 2 weeks), and the submission date will be displayed on myStudies .

• The main supervisor must confirm the thesis in myStudies.

The supervisor must confirm the thesis in myStudies for the student to be able to formally begin the Master's thesis. The student office approves the registration in myStudies. Students can start the Master's Thesis only when the status in myStudies is 'Definite'.

• Submission and evaluation

The supervisor will, subject to the consent of the co-supervisor, communicate the grade and the grading sheet(s) for a thesis to the Study Administration within eight weeks after submission, and preferably sooner. The supervisor and co-supervisor must send the grading sheet(s) to the student. They will commonly meet with the student in person or online to provide more detailed feedback.

• Awarding credit points

Students will be awarded 30 ECTS credit points upon successfully completing the thesis.

• Publication in the ETH Research Collection

Students have the opportunity to publish their Master's thesis in the ETH Research Collection. To publish Master's theses in the Research Collection, a letter of recommendation from the main supervisor is required.

• Degree request

Once the Master's thesis is successfully completed and all credits are obtained, students may request their diploma .

The Master's thesis will be graded, and this grade will serve as the student's performance assessment for the lecture unit. Theses are graded on a scale from 1 - 6. Students must earn a 4 or higher in order to pass.

Only the written Master's thesis is evaluated. Presentation of the Master's thesis is not compulsory; however, the ISTP encourages students to present their thesis in a seminar or a poster presentation.

The Master's thesis Download assessment form (PDF, 253 KB) vertical_align_bottom will state the criteria that will be used to evaluate the thesis.

The supervisor  and co-supervisor will evaluate a student's thesis separately. The scores for each criterion are averaged. The average of all of these scores will constitute the final grade. The main supervisor will be responsible for coordinating the grading process and for submitting the student's final grade to the Study Administration.

A Master's thesis that receives a grade lower than 4 may only be repeated once. If repeated, it must address a new theme. The repetition may proceed under a different supervisor and/or co-​supervisor. Repeating a Master's thesis that has received a grade of 4 or higher is not possible.

Master's Thesis Interviews

To gain deeper insight into how the Master's thesis process could look like, check out our interviews with previous Master's students:

• A thesis abroad: Bridging technology decision making and local engagement in Laos

Outstanding Master’s theses are honored with the Silver Medal of ETH Zurich and a financial sum. Please find the directives here. Past STP programme medal recipients include:

• Felix  Zaussinger,  MSc 2021 ( 2022 Medal Recipient)

Since the number of medals awarded is capped, the D-GESS is typically allocated with one medal over the three MA programs (MA CIS, MA GPW and MSc STP) each year. The directors of study will nominate the candidates and take a joint decision. The ETH Medal will be awarded at the Master's degree graduation ceremony.

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Department of Computer Science

Semester and master's thesis projects.

The Semester Project and the Master's Thesis are mandatory courses of the Master's programme in Cyber Security. They have to be supervised by a professor of the cyber security faculty list .

Semester Project

Before starting, the project must be registered and a project description must be uploaded via myStudies.

Master's Thesis

The Master's Thesis requires 6 months of full time study/work, and we strongly discourage you from attending any courses in parallel. We recommend that you acquire all course credits before the start of the Master’s Thesis.  

Before starting the Master’s Thesis, it is important to agree with your supervisor on the task and the assessment scheme. Both have to be documented thoroughly. You electronically register the Master’s Thesis in myStudies.

Further details on internal regulations of the Master’s Thesis can be downloaded from the following website: www.inf.ethz.ch/studies/forms-and-documents.html .

Information Security Group

• Prof. Dr. David Basin

System Security Group

• Prof. Dr. Srdjan Capkun

Applied Cryptography Group

• Prof. Dr. Kenny Paterson

Network Security Group

• Prof. Dr. Adrian Perrig

Secure & Trustworthy Systems Group

• Prof. Dr. Shweta Shinde

Secure and Private AI (SPY) Lab

• external page Prof. Dr. Florian Tramèr call_made

Information Security and Cryptography Research Group

• Prof. Dr. Ueli Maurer

Foundations of Cryptography Group

• Prof. Dr. Dennis Hofheinz

Computer Security Group

• Prof. Dr. Kaveh Razavi

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Energy Systems Analysis

Congratulations to christoph domenig for winning the swiss association for energy economics’ student award for his master’s thesis.

In his thesis, “A techno-economic analysis of energy communities in multi-family buildings under different European collective self-consumption frameworks,” Christoph developed an optimization model for renter-occupied multi-family buildings, considering investments in low-carbon supply and storage technologies and demand-side measures, such as building envelope retrofits.

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Department of Mathematics

Doctoral theses.

About twenty to thirty doctoral students complete their doctoral thesis at the Department of Mathematics every year.

Recent doctoral examinations

Dissertations

Published after 1 January 2014. For theses published before 2014, please refer to the Research Collection .