Abrar Admin

TU Delft

.jobdescription td { padding: 0 5px; } .jobdescription * { border: none !important; border-width: 0 !important; font-size: 12px !important; font-family: Arial, Helvetica, sans-serif !important; color: black !important; } .jobdescription h1 b, .jobdescription h2 b, .jobdescription h3 b, .jobdescription h4 b, .jobdescription h1, .jobdescription h2, .jobdescription h3, .jobdescription h4 { font-size: 14px !important; font-weight: bold; margin-bottom: 0.5em !important; }
#search-wrapper{display:none;}
/* TUDelft Sidebar style */ .jobColumnTwo .joblayouttoken { background: #e3e3e3; color: #011b3c; padding: 0 20px 5px !important; } .jobColumnTwo .joblayouttoken .joblayouttoken-label { color: #039fd8; font-weight: bold; } .jobColumnTwo .joblayouttoken.marginTopLarge { padding: 20px 20px 5px 20px !important; } .jobColumnTwo .joblayouttoken.marginBottomLarge { padding: 0 20px 20px 20px !important; }
/* TU Delft full-width header image */ .topleft.verticallyscaled.backgroundimage.large-image-component { height: 0 !important; } div[role='img'] .topleft.scaled.large-image-component{ height: 0 !important; position: absolute; padding-top: 20% !important; background-position: center !important; top: 50px; } div.job{ position: relative; padding-top: 26% !important; } /* Fix voor niet werkende knop */ div.jobTitle{ z-index: 2; position: relative; margin-top: 5px; }
Postdoc Trustworthy Graph Machine Learning
Trustworthy Graph Machine Learning for Population Scale Networks
Job description
We invite applications for a postdoctoral researcher to work on fundamental techniques for trustworthy graph machine learning for the analysis of population-scale networks. The position focuses on two pillars of trustworthiness: explainability and privacy-preserving learning.
This research direction connects closely to ongoing work by Dr. Megha Khosla on trustworthy graph machine learning, especially on the relationship between transparency and privacy in graph-based models. Population-scale network data are highly relational and often sensitive. Graph models for such data must therefore be accurate, interpretable and designed to reduce privacy risks.
A central aim of the position is to develop explainability methods for graph machine learning as a form of decision support. These methods should help researchers understand both model behaviour and the underlying data. They should explain why a model makes a prediction, what structural or demographic patterns the model captures, and when its decisions are reliable enough to support scientific interpretation or decision-making.
At the same time, explanations and learned graph representations can themselves reveal sensitive information. In population-scale networks, privacy risks may arise from rare individuals, sensitive attributes, neighbourhood structures etc.The postdoc will therefore investigate how explanations and graph learning methods can be made privacy-aware. This may include studying privacy risks in develoed models, designing explanations that avoid unnecessary disclosure, or developing new privacy-preserving graph learning techniques.
The project is funded by Macroscope, a Dutch national research infrastructure for studying social change, misinformation and trust at population scale.
We are especially interested in candidates with strong expertise in either explainable graph machine learning or privacy-preserving graph learning, together with a willingness to collaborate across the other area.
You will work with the task PI, Dr. Megha Khosla, and her team of PhD and Master&rsquo;s students. You will also collaborate with scientists from different fields across the Macroscope project, including computer science and computational social science. You will also get opportunities to expand your research network within the Computer Science departments and across the broader TU Delft research community.
Job requirements
PhD in computer science, AI, machine learning, data science, network science, computational social science, or a related field.
Expertise in either explainable graph machine learning or privacy-preserving graph learning.
Willingness to develop expertise across the other area.
Strong programming skills in Python, with experience using tools such as PyTorch, PyTorch Geometric, DGL, NetworkX, or scikit-learn.
Engineering skills and willingness/patience to work with large, noisy datasets, including preprocessing, pipeline development, and scalable evaluation.
Ability to work in an interdisciplinary team and communicate research clearly in English.
TU Delft (Delft University of Technology)
Working at TU Delft means contributing to solutions that really make a difference.
For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow. These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.
At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional. Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.
Faculty of Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment &ndash; which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.
, Mathematics and Computer Science.
Conditions of employment
Duration of contract is 2 years Temporary
A job of 38 hours per week.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
An excellent pension scheme via the ABP.
The possibility to compile an individual employment package every year.
Discount with health insurers on supplemental packages.
Flexible working week.
Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
Plenty of opportunities for education, training and courses.
Partially paid parental leave
Attention for working healthy and energetically with the vitality program.
Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands. .
Additional information
If you would like more information about this vacancy or the selection procedure, please contact Dr. Megha Khosla, via m.khosla@tudelft.nl.
Application procedure
Are you interested in this vacancy? Please apply no later than 26 July 2026 upload the following documents:
CV
Motivational letter
Research statement describing your own ambitions for the research line you would like to pursue, and explaining how this position would help you develop and achieve those ambitions.
You can address your application to Dr. Megha Khosla.
Please note:
You can apply online. We will not process applications sent by email and/or post.
As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
Please do not contact us for unsolicited services.
<br><div><div><div><div><div>Faculty/Department: Faculty of Electrical Engineering, Mathematics &amp; Computer Science
</div></div></div></div><div><div><div><div>Salary range: &euro;3546 - &euro;5538
</div></div></div></div><div><div><div><div>Hours per week: 38
</div></div></div></div><div><div><div><div>FTE: 1
</div></div></div></div><div><div><div><div>Submission is possible until: 26 Jul 2026
</div></div></div></div><div><div><div><div>ID job: 3547
</div></div></div></div></div><div></div>.videocomponenta2f51048d3f8cbf3 a{ border: 1px solid transparent; } .videocomponenta2f51048d3f8cbf3 a:focus{ border: 1px dashed #00a6d6 !important; outline: none !important; }

Postdoc Trustworthy Graph Machine Learning

.jobdescription td { padding: 0 5px; } .jobdescription * { border: none !important; border-width: 0 !important; font-size: 12px !important; font-family: Arial, Helvetica, sans-serif !important; color: black !important; } .jobdescription h1 b, .jobdescription h2 b, .jobdescription h3 b, .jobdescription h4 b, .jobdescription h1, .jobdescription h2, .jobdescription h3, .jobdescription h4 { font-size: 14px !important; font-weight: bold; margin-bottom: 0.5em !important; }
#search-wrapper{display:none;}
/* TUDelft Sidebar style */ .jobColumnTwo .joblayouttoken { background: #e3e3e3; color: #011b3c; padding: 0 20px 5px !important; } .jobColumnTwo .joblayouttoken .joblayouttoken-label { color: #039fd8; font-weight: bold; } .jobColumnTwo .joblayouttoken.marginTopLarge { padding: 20px 20px 5px 20px !important; } .jobColumnTwo .joblayouttoken.marginBottomLarge { padding: 0 20px 20px 20px !important; }
/* TU Delft full-width header image */ .topleft.verticallyscaled.backgroundimage.large-image-component { height: 0 !important; } div[role='img'] .topleft.scaled.large-image-component{ height: 0 !important; position: absolute; padding-top: 20% !important; background-position: center !important; top: 50px; } div.job{ position: relative; padding-top: 26% !important; } /* Fix voor niet werkende knop */ div.jobTitle{ z-index: 2; position: relative; margin-top: 5px; }
PhD Position Second Life of Batteries for Grid /Support
Inegrating batteries into traction grids is finding new applications with the integration of RES and third-party users. Still, there are many power electronics and EMS challenges to solve.
Job description
While the concept of reusing electric vehicle batteries for grid support is gaining traction, practical implementation remains limited by a range of unresolved challenges. Existing DC charging systems are not designed for the heterogeneous nature of second-life batteries, which differ in state of health, capacity, and interface standards. Furthermore, spatial constraints in dense urban environments, coupled with regulatory uncertainties surrounding battery transport, safety, and installation, complicate deployment. Current assessment frameworks insufficiently capture the long-term reliability, environmental trade-offs, and techno-economic feasibility of second-life battery systems in grid applications. As a result, there is a pressing need for rigorous research to develop integration strategies, modeling approaches, and regulatory frameworks that enable reliable and scalable use of second-life batteries in high-power DC charging networks.
This PhD is funded by Holland High Tech and ABB Delft.
The research in the Department of Electrical Sustainable Energy is inspired by the technical, scientific, and societal challenges originating from the transition towards a more sustainable society and focuses on four areas:
DC Systems, Energy Conversion and Storage (DCE&amp;S)
Photovoltaic Materials and Devices (PVMD)
Intelligent Electrical Power Grids (IEPG)
High Voltage Technologies (HVT)
The department owns a large ESP Laboratory assembling High Voltage testing, DC Grids testing environment, and large RTDS that is actively used for real-time simulation of future electrical power systems, AC and DC protection and wide-area monitoring and protection. The DC Systems, Energy Conversion and Storage (DCE&amp;S) group is responsible for research and education in the fields of DC systems, high voltage technology, energy storage, electronic power conversion (power electronics), and electromechanics. DC systems is a multidisciplinary field of research, exploring the integration of renewable energy sources and energy storage (electric vehicles) in DC networks and systems and future DC transmission grids. The group is currently active in applications such as Direct Current distribution and transmission grids and microgrids, electrification of mobility (charging of electric vehicles), and renewable generation of electrical energy (such as wind and solar energy). Would you like to know more about the ESE department and the DCE&amp;S group? Please take a look at the webpage www.tudelft.nl/ewi/ese.
Job requirements
Who are we looking for?
You have a master's degree in Electrical Engineering discipline from a well-established university.
An experience with the modeling of one or more among: Batteries, power flows in DC grids, and EV charging demand.
A solid background in power electronics and the development of experimental setups.
Excellent English and programming skills are a requirement. Knowledge of Dutch is an advantage.
A combination of excellent mathematical and analytical skills.
TU Delft (Delft University of Technology)
Working at TU Delft means contributing to solutions that really make a difference.
For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow.
These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.
At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional.
Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.
Faculty of Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment &ndash; which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.
, Mathematics and Computer Science.
Conditions of employment
Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from &euro;3059 - &euro;3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.
Additional information
If you would like more information about this vacancy or the selection procedure, please contact Dr. Zian Qin, via Z.Qin-2@tudelft.nl. For information about the selection procedure, please contact Sharmila Rattansingh, management assistant email: s.rattansingh@tudelft.nl.
Application procedure
Are you interested in this vacancy? Please apply no later than 22 July 2026 upload the following documents:
CV
Motivational letter that explains your personal motivation in pursuing a PhD in general, and this topic in specific, and why you would be an excellent fit to the job requirements. Please do not use ChatGPT or other tools for providing a standard/non-personalized letter
A list of grades of your qualifying degrees (BSc, MSc)
You can address your application to Dr. Zian Qin. Please note that applications will be assessed on a rolling basis and suitable candidates will be invited for interview, so it is recommended not to wait until the deadline with your application.
Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.
Please note:
You can apply online. We will not process applications sent by email and/or post.
As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
Please do not contact us for unsolicited services.
<br><div><div><div><div><div>Faculty/Department: Faculty of Electrical Engineering, Mathematics &amp; Computer Science
</div></div></div></div><div><div><div><div>Salary range: &euro;3059 - &euro;3881
</div></div></div></div><div><div><div><div>Hours per week: 38-40
</div></div></div></div><div><div><div><div>FTE: 1
</div></div></div></div><div><div><div><div>Submission is possible until: 22 Jul 2026
</div></div></div></div><div><div><div><div>ID job: 3525
</div></div></div></div></div><div></div>.videocomponenta2f51048d3f8cbf3 a{ border: 1px solid transparent; } .videocomponenta2f51048d3f8cbf3 a:focus{ border: 1px dashed #00a6d6 !important; outline: none !important; }

PhD Position Second Life of Batteries for Grid /Support

.jobdescription td { padding: 0 5px; } .jobdescription * { border: none !important; border-width: 0 !important; font-size: 12px !important; font-family: Arial, Helvetica, sans-serif !important; color: black !important; } .jobdescription h1 b, .jobdescription h2 b, .jobdescription h3 b, .jobdescription h4 b, .jobdescription h1, .jobdescription h2, .jobdescription h3, .jobdescription h4 { font-size: 14px !important; font-weight: bold; margin-bottom: 0.5em !important; }
#search-wrapper{display:none;}
/* TUDelft Sidebar style */ .jobColumnTwo .joblayouttoken { background: #e3e3e3; color: #011b3c; padding: 0 20px 5px !important; } .jobColumnTwo .joblayouttoken .joblayouttoken-label { color: #039fd8; font-weight: bold; } .jobColumnTwo .joblayouttoken.marginTopLarge { padding: 20px 20px 5px 20px !important; } .jobColumnTwo .joblayouttoken.marginBottomLarge { padding: 0 20px 20px 20px !important; }
/* TU Delft full-width header image */ .topleft.verticallyscaled.backgroundimage.large-image-component { height: 0 !important; } div[role='img'] .topleft.scaled.large-image-component{ height: 0 !important; position: absolute; padding-top: 20% !important; background-position: center !important; top: 50px; } div.job{ position: relative; padding-top: 26% !important; } /* Fix voor niet werkende knop */ div.jobTitle{ z-index: 2; position: relative; margin-top: 5px; }
Assistant Professor in Biophysics of Living Systems
Challenge: Understand how life emerges from molecular interactions.
Change: Combine physics and biology to decode cells at the nanoscale.
Impact: New insights into disease and the fundamentals of life.
Job description
Imagine watching the inner workings of a living cell, where the fundamental laws of physics meet the complexity of life at the nanoscale. Since 2010, the Department of Bionanoscience at Delft University of Technology has been on a pioneering quest to decode these principles. We are a multidisciplinary and international community of scientists driven by a singular mission: to understand how interactions at the smallest scales give rise to biological function or the onset of disease. From observing the dance of single molecules to the bottom-up construction of synthetic cells, we bridge the gap between physics and the full complexity of living systems. Now, we invite you to join our group of 19 Principal Investigators at TU Delft to help us write the next chapter in our understanding of Life.
The Department of Bionanoscience, part of the Kavli Institute of Nanoscience Delft, is a world-leading environment for fundamental research at the interface of biology and physics. We focus on biological processes from the level of single molecules to the full complexity of living cells. We seek an early career Principal Investigator who has demonstrated excellence in experimental research and thrives on conducting original research with impact, geared to understanding how life works, either at the molecular or cellular level. We encourage applications from researchers with a biophysics-oriented perspective or approach. Harnessing your communication skills, you inspire and convince funding agencies and partners of your vision and research. You actively seek collaboration with relevant faculties, universities and external stakeholders. In addition, you enjoy mentoring, teaching and interacting with students, while continuously developing yourself and your academic career. Your research will benefit from our in-house facilities, including a central optical microscopy, a cell culture, a protein purification, a cryo-EM, mass spectrometry, flowcytometry, and the Kavli Nanolab Delft cleanroom. Our laboratory space is located in a modern building with dedicated lab areas for building and operating sensitive physical instrumentation.
As a Principal Investigator, you will:
Establish an independent experimental research line that is complementary to our current strengths in single-molecule biophysics, synthetic biology, and quantitative cell biology.
Secure external funding through competitive grants (e.g., NWO Vidi, ERC StG) to build and lead a team of PhD students, Postdocs and Technicians.
Provide excellent education by teaching and developing courses for our unique BSc and MSc programs in Nanobiology; a program at the interface of biology, physics and math.
Contribute to a collaborative culture, interacting synergistically with existing research groups and participating in the management of the department and our educational program(s).
Job requirements
The ideal candidate is a creative experimentalist who thrives on scientific and engineering challenges. You should possess:
A PhD in a relevant field (e.g., Biophysics, Biochemistry, Cell biology, Bionanotechnology) and relevant post-doctoral experience.
An outstanding scientific track record, evidenced by high-quality publications.
A clear vision for a new, independent experimental research line that uses advanced methodology to probe, manipulate or engineer cellular life or its components.
A passion for education and the ability to inspire students in an international environment.
Obtain the University Teaching Qualification (UTQ) within three years.
TU Delft (Delft University of Technology)
Working at TU Delft means contributing to solutions that really make a difference.
For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow.
These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.
At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional.
Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.
Faculty Applied Sciences
With more than 1,100 employees, including 150 pioneering principal investigators, as well as a population of about 3,600 passionate students, the Faculty of Applied Sciences is an inspiring scientific ecosystem. Focusing on key enabling technologies, such as quantum- and nanotechnology, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st century. To that end, we educate innovative students in broad Bachelor's and specialist Master's programmes with a strong research component. Our scientists conduct ground-breaking fundamental and applied research in the fields of Life and Health Science &amp; Technology, Nanoscience, Chemical Engineering, Radiation Science &amp; Technology, and Engineering Physics. We are also training the next generation of high school teachers.
 about this vacancy or the selection procedure, please contact Martin Depken, Chair Department Bionanoscience, via or S.M.Depken@tudelft.nl.
Application procedure
Are you interested in this vacancy? Please apply no later than 30 July 2026 upload the following documents:
Motivation letter (max 2 pages).
Detailed CV and a full publication record.
Research plan outlining your vision for an experimental program in the physics of life (max. 3 pages).
Teaching statement describing your educational philosophy and ambitions (max. 1 page).
We encourage you to apply as soon as possible, as we will begin contacting applicants while the vacancy is still open. Due to the summer break, interviews are scheduled to take place in September.
You can address your application to Martin Depken, Chair Department Bionanoscience.
Please note:
You can apply online. We will not process applications sent by email and/or post.
As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
Please do not contact us for unsolicited services.
<br><div><div><div><div><div>Faculty/Department: Faculty of Applied Sciences
</div></div></div></div><div><div><div><div>Salary range: &euro;4728 - &euro;6433
</div></div></div></div><div><div><div><div>Hours per week: 32-38
</div></div></div></div><div><div><div><div>FTE: 0,8-1,0
</div></div></div></div><div><div><div><div>Submission is possible until: 30 Jul 2026
</div></div></div></div><div><div><div><div>ID job: 3428
</div></div></div></div></div><div></div>.videocomponenta2f51048d3f8cbf3 a{ border: 1px solid transparent; } .videocomponenta2f51048d3f8cbf3 a:focus{ border: 1px dashed #00a6d6 !important; outline: none !important; }

Assistant Professor in Biophysics of Living Systems

Join TU Delft and explore 3   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

TU Delft

About Company

Postdoc Trustworthy Graph Machine Learning

PhD Position Second Life of Batteries for Grid /Support

Assistant Professor in Biophysics of Living Systems