PhD on develop an agent-based digital twin platform for collective energy transition decisions

Introduction
Are you passionate about leveraging AI and digital tools for sustainability transitions and developing decision support systems to accelerate collective energy transition? Join our team to drive innovations that support urban resilience. This is your chance to make a real impact!

Job Description
The energy and the climate crisis reinforced the urgency of energy efficiency in residential buildings in Europe. To meet its climate targets, the Netherlands needs to decarbonize the residential sector. This requires that many distributed actors (households, owners associations, social housing associations, and citizen collectives) invest in energy transition rapidly and at scale. Yet citizens’ collective (housing associations, homeowners' associations, etc.) investments in energy-related home renovation will impact integrated energy systems, including correlations between energy grids, uncertainties and simultaneous peak loads. In this project, Digital pathways for accelerating collective decision making of energy renovation in the built environment (DPARt): Through data-driven and user-centric design approach for VvEs, we explore a promising solution.

Sustainability, in its broadest definition, is the cornerstone of research and education in the Department of Built Environment. We take the lead in (re)shaping the built environment to be future-proof, safe, healthy, inclusive and respectful of planetary boundaries. We house the entire spectrum of technology, engineering, design, and human behavior disciplines in the built environment, with world-class experimental facilities at all scales. This allows us to address societal challenges from a uniquely integrated perspective.

Job responsibilities

• Transforms floorplans and construction drawings of buildings into geo-data, and generate potential energy efficiency improvement options, and visualize for end users.
• Develop an agent-based digital twin platform of VvEs to support the energy transition decision making.
• Further develop agent-based model for collective decision-making process addressing uncertainties and validating in living labs.
• Design narrative dynamics for serious games incorporating AI agents for effective interactive communication.
• Publishing articles in high-quality scientific journals.
• Coordination of research activities.
• You will be contributing to the Urban Informatics research theme at the chair of Information Systems in the Built Environment (ISBE).

Job Requirements

• A master’s degree (or an equivalent university degree) in Building engineer or Environmental Science, Planning, Engineering, computer science, innovation science or related fields with demonstrable experience in spatial analysis and numerical modelling of the environments.
• A research-oriented attitude.
• Solid programming knowledge (Python, and preferably web development languages), and some experience with ABM or willing to learn ABM is a plus
• A good understanding of AI techniques, especially open for new challenges.
• Ability to work in an interdisciplinary team and interested in collaborating with societal partners.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level). Knowledge of Dutch language is useful to connect with societal partners and test the developed model in the living labs.
• A positive attitude and good communication skills.
• Excellent interpersonal skills, with the ability to work in a team and on own initiative.

Conditions of Employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

About us
Eindhoven University of Technology is a leading international university within the Brainport region where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager, dr. Qi Han, q.han@tue.nl or dr. Dujuan Yang, D.Yang@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact Leo van Houten, HR-Advisor, l.v.houten@tue.nl or +31 40 247 8269.

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.

PhD In Immunomodulation for In Situ Tissue Regeneration

Introduction

• Are you inspired by the potential to use degradable synthetic implants that are transformed into living tissues by the body itself?
• Are you fascinated by our ability to use the immune system to our advantage to induce tissue regeneration in situ?
• Are you eager to contribute to better and sustainable healthcare?
• Are you passionate about inspiring and mentoring students and working in a high-end collaborative and interdisciplinary research environment?
• Are you our next PhD in Immunomodulation for Tissue Regeneration?

Job Description
There is an increasing clinical demand for sophisticated medical implants and the scientific field of implant technology is exponentially growing. The main challenge is to harness the immune response to such an implant. In this research we use the immune response to our advantage, by using bioresorbable synthetic biomaterials that are gradually replaced by living tissue, directly at the functional site in the body, or in situ. Our research on this technology has, for example, led to the world’s first clinical trials using regenerative heart valves for children with congenital cardiac malformations.

While tremendous progress has been made in terms of manufacturing technologies for biomaterials and implants, there is relatively little progress in terms of fundamentally understanding the inflammatory and regenerative process in vivo. The various cellular interactions in in situ tissue engineering, and how these are influenced by (1) the local niche (i.e. biomaterial and extracellular matrix environment) and (2) systemic factors (e.g. immunological state), are largely overlooked to date. Moreover, preclinical in vivo studies have yielded unexplained variabilities in outcome. This raises the question to what extent patient-specific systemic aspects influence the local immunological and regenerative processes. The main aim of your research will be to delineate the combined influences of systemic immunity and local immunomodulation on the process of in situ tissue regeneration at the local tissue site, in order to (i) enable the elucidation of patient-specific immunity on in situ tissue regeneration, and (ii) enable the (precision) targeting of systemic immunity to steer the regenerative process at any time during implantation.

Embedding
You will be embedded in a highly inspiring research environment, both socially and professionally, which facilitates access to high-end research facilities, as well as fosters interdisciplinary collaborations. Your project is part of the DRIVE-RM research program (NWO Summit) and will run in close collaboration with partners from University Medical Center Utrecht. You will be an integral member of the ImmunoRegeneration team and the overarching Soft Tissue Engineering and Mechanobiology research group (headed by Prof. Carlijn Bouten) at our Department. Moreover, you will be affiliated to the Institute for Complex Molecular Systems, our interdepartmental center for research excellence.

The Department of Biomedical Engineering offers top-level education and research in one of the most relevant and exciting scientific disciplines of the 21st century: engineering health. In combining engineering and life sciences, through challenge-based learning and a multidisciplinary approach in collaboration with hospitals, industry and others, the department addresses the great challenges of the future, striving to improve healthcare and society as a whole.

Job Requirements

• A master’s degree (or an equivalent university degree) in Biomedical Engineering.
• A research-oriented attitude.
• Experience in cell culture is a must. Expertise/training in immunology and/or tissue regeneration is strongly preferred.
• Ability to work in a multidisciplinary team with researchers at different academic levels (MSc, PhD, Post-doc).
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

Conditions of Employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881 gross per month).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

About us
Eindhoven University of Technology is a leading international university within the Brainport region where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact Anthal Smits, Associate Professor of ImmunoRegeneration, a.i.p.m.smits@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact Sascha Sanchez, HR advisor, s.j.m.g.sanchez.van.oort@tue.nl.

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.

PhD on develop an agent-based digital twin platform for collective energy transition decisions

The energy and the climate crisis reinforced the urgency of energy efficiency in residential buildings in Europe. To meet its climate targets, the Netherlands needs to decarbonize the residential sector. This requires that many distributed actors (households, owners associations, social housing associations, and citizen collectives) invest in energy transition rapidly and at scale. Yet citizens’ collective (housing associations, homeowners' associations, etc.) investments in energy-related home renovation will impact integrated energy systems, including correlations between energy grids, uncertainties and simultaneous peak loads. In this project, Digital pathways for accelerating collective decision making of energy renovation in the built environment (DPARt): Through data-driven and user-centric design approach for VvEs, we explore a promising solution.

Sustainability, in its broadest definition, is the cornerstone of research and education in the Department of Built Environment. We take the lead in (re)shaping the built environment to be future-proof, safe, healthy, inclusive and respectful of planetary boundaries. We house the entire spectrum of technology, engineering, design, and human behavior disciplines in the built environment, with world-class experimental facilities at all scales. This allows us to address societal challenges from a uniquely integrated perspective.

Job responsibilities

• Transforms floorplans and construction drawings of buildings into geo-data, and generate potential energy efficiency improvement options, and visualize for end users.
• Develop an agent-based digital twin platform of VvEs to support the energy transition decision making.
• Further develop agent-based model for collective decision-making process addressing uncertainties and validating in living labs.
• Design narrative dynamics for serious games incorporating AI agents for effective interactive communication.
• Publishing articles in high-quality scientific journals.
• Coordination of research activities.
• You will be contributing to the Urban Informatics research theme at the chair of Information Systems in the Built Environment (ISBE).

PhD In Machine Learning for Drug Discovery in Low-Data Regimes

Introduction
We invite applications for a fully funded PhD position within the LowDataML doctoral network, focusing on developing innovative machine-learning approaches for drug discovery under low-data conditions. LowDataML aims to bridge the gap between current ML/AI tools — which typically require large, dense datasets — and the realities of lab-scale chemistry and early-stage drug research, where data are often scarce, sparse or incomplete.

Job Description
Your tasks will include:

• Developing and benchmarking ML/AI algorithms tailored to low-data regimes — e.g. few-shot learning, transfer learning or data-efficient representation learning — for prediction of molecular properties, activity, or synthetic feasibility.
• Working at the interface of cheminformatics, synthetic chemistry and drug discovery, collaborating with partners across academia and industry.
• Contributing to accelerating the discovery of new therapeutics with machine learning.
• Communicating the results of your research through publications in scientific journals and presentations at conferences.

You will work at the interface between AI, chemistry, and biology, with a proactive and interdisciplinary attitude. You will become a member of the Molecular Machine Learning team (led by Prof. F. Grisoni), whose mission is to augment human intelligence in drug discovery with novel AI technology. You will also be embedded in the Chemical Biology group (led by Prof. L. Brunsveld), the Dept. of Biomedical Engineering, the Institute for Complex Molecular Systems, and the Eindhoven AI Systems Institute, which are characterized by a highly interdisciplinary and collaborative approach to science and research.

The Department of Biomedical Engineering offers top-level education and research in one of the most relevant and exciting scientific disciplines of the 21st century: engineering health. In combining engineering and life sciences, through challenge-based learning and a multidisciplinary approach in collaboration with hospitals, industry and others, the department addresses the great challenges of the future, striving to improve healthcare and society as a whole.

Job Requirements
Background:

• An MSc degree (or equivalent) in Chemistry, Medicinal Chemistry, Chemical Engineering, Cheminformatics, Bioinformatics, Computer Science, or a related discipline.
• Foundational understanding of organic chemistry, molecular structure, and/or drug-discovery principles.
• Demonstrated interest in applying machine learning or computational methods to chemical or biological problems.
• Motivation to work with low-data, sparse, or noisy datasets, typical in early-stage drug discovery.

Technical skills:

• Proficiency in Python (required).
• Practical experience with machine learning or deep learning workflows (required).
• Familiarity with ML frameworks such as PyTorch, TensorFlow, or scikit-learn (required).
• Experience with cheminformatics tools such as RDKit (required or strongly desirable).
• Basic knowledge of data handling, version control (e.g., Git), and reproducible scientific programming (desirable).
• Understanding of molecular representations (e.g., fingerprints, SMILES, graphs) and/or computational chemistry concepts (desirable).
• Familiarity with chemical or biological databases (e.g., ChEMBL, PubChem, PDB) is a plus.
• Experience with Bayesian modelling, transfer learning, few-shot learning, or other data-efficient ML methods is advantageous but not required.

Soft skills:

• A research oriented and quantitative thinking attitude.
• Proven ability to work in interdisciplinary teams.
• Good writing and presentation skills.
• Ability and willingness to collaborate in an international, interdisciplinary work environment.
• Fluent in spoken and written English (C1 level).

Conditions of Employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

About us
Eindhoven University of Technology is a leading international university within the Brainport region where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager dr. Francesca Grisoni, f.grisoni@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact Sascha Sanchez, HR advisor, s.j.m.g.sanchez.van.oort@tue.nl.

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.
• A list of 1 to 3 selected publications (e.g., preprints, thesis manuscript, peer-reviewed papers, etc) along with a summary of their content, a description of their relevance for the scopes of the project, your role in the research, and the corresponding DOIs (if available). Preprints and conference papers can be included

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.

PhD In Immunomodulation for In Situ Tissue Regeneration

There is an increasing clinical demand for sophisticated medical implants and the scientific field of implant technology is exponentially growing. The main challenge is to harness the immune response to such an implant. In this research we use the immune response to our advantage, by using bioresorbable synthetic biomaterials that are gradually replaced by living tissue, directly at the functional site in the body, or in situ. Our research on this technology has, for example, led to the world’s first clinical trials using regenerative heart valves for children with congenital cardiac malformations.

While tremendous progress has been made in terms of manufacturing technologies for biomaterials and implants, there is relatively little progress in terms of fundamentally understanding the inflammatory and regenerative process in vivo. The various cellular interactions in in situ tissue engineering, and how these are influenced by (1) the local niche (i.e. biomaterial and extracellular matrix environment) and (2) systemic factors (e.g. immunological state), are largely overlooked to date. Moreover, preclinical in vivo studies have yielded unexplained variabilities in outcome. This raises the question to what extent patient-specific systemic aspects influence the local immunological and regenerative processes. The main aim of your research will be to delineate the combined influences of systemic immunity and local immunomodulation on the process of in situ tissue regeneration at the local tissue site, in order to (i) enable the elucidation of patient-specific immunity on in situ tissue regeneration, and (ii) enable the (precision) targeting of systemic immunity to steer the regenerative process at any time during implantation.

Embedding
You will be embedded in a highly inspiring research environment, both socially and professionally, which facilitates access to high-end research facilities, as well as fosters interdisciplinary collaborations. Your project is part of the DRIVE-RM research program (NWO Summit) and will run in close collaboration with partners from University Medical Center Utrecht. You will be an integral member of the ImmunoRegeneration team and the overarching Soft Tissue Engineering and Mechanobiology research group (headed by Prof. Carlijn Bouten) at our Department. Moreover, you will be affiliated to the Institute for Complex Molecular Systems, our interdepartmental center for research excellence.

The Department of Biomedical Engineering offers top-level education and research in one of the most relevant and exciting scientific disciplines of the 21st century: engineering health. In combining engineering and life sciences, through challenge-based learning and a multidisciplinary approach in collaboration with hospitals, industry and others, the department addresses the great challenges of the future, striving to improve healthcare and society as a whole.