BIM-SHM 与智能传感器系统方向博士职位 (REUNATECH DC4)

Ageing infrastructures, urbanization, and climate change are intensifying the vulnerability of critical infrastructures (CI), high-tech industries (HTI), and communities to cascading hazards, particularly NaTech (Natural Hazard Trig-gering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the new generation of Doctoral Candidates (DCs) capable of tackling these challenges through cutting-edge interdisciplinary research and innovation. REUNATECH brings together leading universities, research institutes, and industrial partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a holistic multi-hazard risk framework capturing cascading effects across systems and scales; (2) the creation of digital environments utilizing real-time data for dynamic risk evaluation; (3) the advancement of risk-to-resilience methodologies ; and (4) the establishment of digital twin-based resilience frameworks for CI, HTI, and urban environments. The network emphasizes innovation through the development of a Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design platforms. Furthermore, REUNATECH promotes trans-disciplinary collaboration via multi-stakeholder platforms, bridging academia, industry, and policy. Through its holistic, digital, and resilience-centered approach, REUNATECH supports the European Green Deal, Sendai Framework, and UN Sustainable Development Goals. DCs will benefit from an immersive training structure comprising cross-sectoral secondments, workshops, and summer schools, enhancing their expertise in NaTech risk and resilience and enabling their integration into European and international research and innovation landscapes. Research Project The research project focuses on developing an integrated BIM-SHM (Building Information Modelling – Structural Health Monitoring) framework tailored for critical infrastructures (CI) exposed to seismic and cascading hazards. The doctoral candidate will design, implement, and validate a real-time structural monitoring and damage visualization system by coupling IoT-enabled dynamic sensors with digital building models. Through the use of decentralized edge computing, cloud-based analytics, and existing seismic networks, the project aims to improve rapid decision-making and resilience assessment during and after seismic events . A key outcome will be a digital twin environment capable of streaming and interpreting dynamic structural performance metrics under multi-hazard conditions, enabling timely risk-informed actions and optimized lifecycle management of CI assets. Objectives DC4 will develop an integrated BIM-SHM framework for real-time structural performance monitoring and dynamic visualization in critical infrastructures. This will involve deploying IoT-enabled smart sensors with decentralized processing to stream high-frequency data into a BIM environment for immediate structural analysis. Advanced algo-rithms such as autoregressive and eigensystem realization techniques will be used for continuous condition assess-ment and model updating. Additionally, cloud-based data handling and integration with regional seismic sensor net-works will enhance processing efficiency, early-warning capability, and stakeholder decision-making.

Requirements / required education level / degree: Master Degree or equivalent

Requirements / required education level / discipline: Engineering

Requirements / skills: • MSc. degree (or equivalent) in Civil Engineering, Structural Engineering, or related fields . • Proven experience or great interest in the topics of Structural Health Monitoring (SHM), Building Information Modelling (BIM), numerical simulations and real-time monitoring systems with the use of sensor technology . • Proficiency and/or interest in programming languages (e.g. MATLAB, Python, R) and software platforms such as Autodesk, ALLPLAN, ANSYS, REVIT, Tekla, Rhino, Grasshopper, etc. • Basic knowledge in the areas of signal processing, time series analysis or machine learning for the interpretation of structural data is desirable. • Basic knowledge of numerical analysis and design of structures for special load cases (earthquakes, explosions) is desirable. • You are fluent in written and spoken English.

Requirements / required languages / language: ENGLISH

Requirements / required languages / language level: Good

Additional information / eligibility criteria: Eligibility criteria The applicant must be a Doctoral Candidate (i.e. not already in possession of a doctoral degree at the date of the recruitment). At the time of recruitment, the researcher must not have resided or carried out their main activity (work, studies, etc.) in the country of their recruiting organization for more than 12 months in the three years immediately prior to the recruitment date. Compulsory national service and/or short stays such as holidays are not considered.

Additional information / selection process: Selection process The selection and recruitment process will be in accordance with the European Charter and Code of Conduct for the Recruitment of Researchers. The recruitment process will be open, transparent, impartial, equitable, and merit based. There will be no overt/covert discrimination based on race, gender, sexual orientation, religion or belief, disability or age. To this end, the following selection criteria will be considered: • Curriculum • Academic performance (diplomas, university transcripts, etc.) • Research and industrial experience • Awards and fellowships • Publications and patents • Research, leadership, and creativity potential • English knowledge • Other relevant items based on the specific candidate

The application deadline is 11th October 2026 23:59 CET . All applications will be analysed after the application deadline, and the shortlisted candidates will be invited to a teleconference interview. At the end of the selection process, all the applicants will be informed of the outcome of their application by return email. DISCLAIMER By applying for this position, the applicants: • Give their consent to circulate their application and personal data within the members of the consortium. • Declare to fulfil the eligibility requirements defined by above. • Agree to spend an academic secondment of 3 months as well as an industrial secondment of another 3 months within the REUNATECH consortium as described. • Agree that they will comply with the planned PhD enrolment.

Each application must include the following material: • Curriculum vitae setting out the educational qualifications as well as any additional scientific achievements and publications. The CV must clearly indicate the applicant’s vitae name, surname, gender, date of birth, nationality, country of residence in the last three years). • Evidence of English proficiency. • Copy of Bachelor’s and Master’s certificates. • Copy of Bachelor’s and Master’s transcripts. • Any additional material useful for the assessment of the candidate (e.g., recommendation letters, research project/statement in agreement with the requirements specified in previous text). All material must be in-cluded in one compiled pdf file. The file must be named Surname_DC4.pdf

he one compiled pdf file should be sent via mail to the following email address: reunatech@rwth-aachen.de

Additional information / comment: The selected applicant will be enrolled into the Ph.D. program at the Chair of Structural Analysis and Dynamics, RWTH Aachen University to conduct the planned research activities. Academic secondment DC4 will undertake a 3-month research secondment at an academic partner of the REUNATECH project. The planned host institution for this secondment is Aristotle University of Thessaloniki, Thessaloniki, Greece . Industrial secondment DC4 will undertake a 3-month research secondment at an industrial partner of the REUNATECH project. The planned host institution for this secondment is ALLPLAN, Germany .

Work location / nr job positions: 1

Work location / job organisation institute: Chair of Structural Analysis and Dynamics, Faculty of Civil Engineering

Work location / job country: Germany

Work location / job city: Aachen

Work location / job postal code: 52074

Work location / job street: Mies-van-der-Rohe-Str. 1

Hiring contact / organisation institute: RWTH Aachen University

Hiring contact / organisation institute type: Higher Education Institute

Hiring contact / country: Germany

Hiring contact / city: Aachen

Hiring contact / postal code: 52056

Hiring contact / street: Templergraben 55

Hiring contact / e mail: reunatech@rwth-aachen.de

Hiring contact / website: https://www.lbb.rwth-aachen.de/go/id/eaxh/?lidx=1

Hiring contact / website: https://www.linkedin.com/company/reunatech/

Application / how to apply: e-mail

Application / application email: reunatech@rwth-aachen.de

EU funding / framework programme: Horizon Europe - MSCA

EU funding / cofund nr job position: 1

EU funding / cofund destination countries: Greece

EU funding / cofund destination countries: Germany

EU funding / sesam agreement number: 101225914

EU funding / job reference number: DC4

Research field / main research field: Engineering

Research field / sub research field: Civil engineering

Researcher profile: First Stage Researcher (R1)

Positions: PhD Positions

Contract: Temporary

Job status: Full-time

Application deadline (as exported; timezone unverified): 2026-10-11T21:59:59