Chalmers University of Technology

Description The SHORES Center at New York University Abu Dhabi (NYUAD) invites applications for a Postdoctoral Associate position in the area of Digital Twins and Artificial Intelligence (AI) for Smart Infrastructure Management Systems to work under the supervision of Professor Borja García de Soto, director of the S.M.A.R.T. Construction Research Group and Co-PI in the SHORES Center. The successful candidate will also collaborate with researchers and other Investigators from the SHORES Center on project related to the advancement of multidisciplinary research supporting the digitalization of the built environment. The selected researcher will expand the current research in the area of AI- and ML-powered digital twin frameworks for civil, energy, and built-environment infrastructure. These frameworks integrate IoT-enabled sensing and real-time analytics to support continuous monitoring, data-driven evaluation, and predictive maintenance. The work also address user comfort and indoor environmental quality (IEQ) as key dimensions of infrastructure performance. This research forms part of a broader effort to design smart, adaptive, and resilient Infrastructure Management Systems that leverage digitalization, automation, and intelligent decision-making. Key Responsibilities include conduct cutting-edge research on the integration of Digital Twins with AI/ML technologies for infrastructure lifecycle management. Develop and validate computational models for monitoring and predicting infrastructure performance. Collaborate with faculty and researchers across SHORES. Disseminate research findings through high-impact publications and conference presentations. Mentor graduate and undergraduate students involved in related projects. Candidates must hold a Ph.D. in Civil Engineering, Computer Science, or a related discipline with a focus on Digital Twins, AI, ML, or smart infrastructure systems. Strong background in computational modeling, data analytics, and/or automation in construction or infrastructure management. Demonstrated research excellence through peer-reviewed publications. Experience with programming languages and software platforms relevant to Digital Twin development (e.g., Python, MATLAB, Revit, Unity, or IoT frameworks). Excellent written and verbal communication skills in English. The terms of employment are competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled. To be considered, applicants must submit the following documents in PDF format: a cover letter, curriculum vitae with a complete list of publications, academic transcript, research statement, sample journal publications, and at least three letters of recommendation. For any questions, please contact garcia.de.soto@nyu.edu. About NYUAD: NYU Abu Dhabi is a degree-granting research university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in their pursuit of academic and scholarly activity. This global university represents a transformative shift in higher education, one in which the intellectual and creative endeavors of academia are shaped and examined through an international and multicultural perspective. As a major intellectual hub at the crossroads of the Arab world, NYUAD serves as a center for scholarly thought, advanced research, knowledge creation, and sharing, through its academic, research, and creative activities. EOE/AA/Minorities/Females/Vet/Disabled/SexualOrientation/Gender Identity Employer UAE Nationals are encouraged to apply.

Job Purpose The Professional Officers Division (POD) houses a centralized pool of academic staff under the Professional Officers scheme. Professional Officers come with specialised and deep technical skills acquired through extensive industry experience. They form the talent pool which brings a much-needed industry perspective to student learning. They facilitate applied learning and applied research in SIT, complementing the academic expertise of the faculty to bring industry practices and applications into the curriculum. Professional Officers leverage on their industry experiences to create authentic learning environments, where discovery and innovation take place. They act as coaches and mentors to students during practical learning activities such as laboratory sessions, Capstone Projects and the Integrated Work Study Programme (IWSP). Professional Officers could also lead or work with faculty on industry innovation projects to provide solutions to the industry. In addition to their role in applied learning and applied research, Professional Officers manage the centralised laboratory facilities and resources in SIT. With Technical Officers, laboratory safety professionals, and administrators in POD, they jointly develop central policies and processes for the safe and seamless operation of laboratories in SIT. Key Responsibilities Design and teach labs & practice modules. Mentor students in Capstone Projects and the Integrated Work Study Programme (IWSP). Lead or co-lead innovation projects with industry. Manage labs and equipment to support academic programmes and applied research. Ensure safety in labs. Job Requirements A good degree in Electronics, Mechatronics, Software Engineering, or a related field. Masters, PhD and/or relevant professional certifications would be advantageous. Deep technical specialist with 10 or more years of working experience in Automation, Robotics, Autonomous Systems, or related areas in development would be preferred. Experience in following areas is highly desirable: Hands-on experience in electronics/electrical. Programming of Microcontrollers and embedded systems. Working knowledge of programming languages such ROS/ROS2, Python, C/C++ Programming, Knowledge of subjects such as computer vision, Machine Learning, Artificial Intelligence and Kinematics and dynamics. Autonomous systems, Robotics and Automation. Industry 4.0 and Internet-of-Things. Advantageous to have prior knowledge in: Hands-on experience implementation of industrial robotics systems and performing offline simulation of robotic work cells. Digitalisation skills – IoT, data analytics, artificial intelligence, machine learning, mixed reality, etc would be advantageous. Programming and simulation software such as MATLAB, Gazebo and Tensor flow. Knowledge of Linux OS. Extensive hands-on experience and knowledge of industry practices and engineering principles to bring industry perspective to SIT. Keen interest in innovation projects, with demonstrated ability in developing solutions to technical problems. Strong supervisory skills and enjoy working closely with students in an educational environment. Demonstrate proficiency to keep abreast of development in the field and pursue professional certification programs. Possess industrial certifications in relevant areas will be an added advantage.

Lingnan University is one of the eight publicly funded institutions in the Hong Kong Special Administrative Region (HKSAR) of the People’s Republic of China (PRC) and has the longest established tradition among the local institutions of higher education. It is widely recognised for providing quality education with a focus on whole-person development and conducting high-impact research for a better world. Moving forward, Lingnan University is well positioned to take lead as a comprehensive university in arts and sciences in the digital era, with impactful research and innovations. Lingnan University offers undergraduate, taught postgraduate, and research postgraduate programmes in the Faculties of Arts, Business, Social Sciences, and the Schools of Data Science, Graduate Studies and Interdisciplinary Studies. To foster interdisciplinary collaboration and scientific progress, Lingnan University established the Lingnan University Institute for Advanced Study (LUIAS), attracting distinguished scholars from around the world to collaborate with its faculty and students. With traditional strengths in arts, business, social sciences, and interdisciplinary studies, the University aims to equip students with practical knowledge and critical thinking skills to thrive in the future. Subsequent to the establishment of the School of Data Science and LUIAS, Lingnan University is transforming into a hub for global leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/. Applications are now invited for the following post: Postdoctoral Fellow - Frontier of AI driven Inverse Design of Functional Materials Wu Jieh Yee School of Interdisciplinary Studies (Post Ref.: 25/176) Professor Xi Chen, Dean of the Wu Jieh Yee School of Interdisciplinary Studies and Chair Professor of Interdisciplinary Studies, leads an interdisciplinary team working at the frontier of AI driven inverse design of functional materials. Current research directions include: Reversible material representation methods for accelerated inverse design Large language, diffusion & graph neural models for materials discovery Fine tuning and architecture optimisation of foundation models Inverse design of next generation functional materials (e.g. energy, sustainability) The group partners closely with leading institutes in Hong Kong, Shenzhen, and worldwide, offering an exciting, collaborative research environment. The appointee will work as part of the team. This involves (1) conducting independent and collaborative research leading to publications in top tier journals and conferences; (2) contributing to grant proposal writing and collaborative projects; and (3) mentoring junior researchers and assisting with laboratory management. Requirements The candidate should have obtained / been conferred a PhD degree or an equivalent qualification in Materials Science, Mechanical / Applied Mechanics, Physics, Computer Science, Data Science, or a closely related field for no more than three years prior to the commencement of the appointment. The candidates should have a strong track record in at least one of the group’s research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential. Additionally, the candidate should possess an excellent command of written and spoken English and demonstrate the ability to work independently as well as part of a multidisciplinary team. Appointment The conditions of appointment will be competitive. Commencing salary will be commensurate with qualifications and experience. Fringe benefits include annual leave, medical and dental benefits, mandatory provident fund, gratuity, and incoming passage and baggage allowance for the eligible appointee. The appointment will normally be made on an initial contract of up to two years. Application Procedure (online application only) Please click "Apply Now" to submit your application. Personal data collected will be used for recruitment purposes only. We are an equal opportunities employer. The review of applications will start and continue until the post is filled. Qualified candidates are advised to submit their applications early for consideration. The University reserves the right not to make an appointment for the post advertised, or to fill the post by invitation or by search. We regret that only shortlisted candidates will be notified.