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.