Metropolitan University Prague

Description We are inviting applications for a Post-doctoral Associate in the Division of Social Science at NYU Abu Dhabi from individuals who have or will soon receive a PhD in Economics with fields of research in Macroeconomics or Computational Social Science. The appointment is for 2 years and will begin September 1, 2026, subject to final budget approval and visa acquisition by the prospective postdoc candidate. The post-doctoral associate will spend half their time on independent research, and half their time on collaborative research with Professors Alaïs Martin-Baillon, Jordan Norris, and Samreen Malik. The collaborative research will be on macroeconomic expectations, with a focus on firms and the role of networks. An ideal candidate may have experience with surveys and have expertise in computational economics. The position does not require teaching, but it may be possible to get teaching experience for compensation. For consideration, applicants must submit a cover letter, curriculum vitae with full publication list, a job market paper, statement of research interests, transcript and two letters of reference, all in PDF format. If you have any questions, please email Professor Martin-Baillon at alais.martin.baillon@nyu.edu and Professor Norris at jjnorris@nyu.edu. About NYU Abu Dhabi 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/Sexual Orientation/Gender Identity Employer UAE Nationals are encouraged to apply

Job Purpose: The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of the research team to develop a Multimodal AI for Fire Detection & Safety Systems. Key Responsibilities:  Participate in and manage the research project with Principal Investigator (PI), Collaborator and the research team members to ensure all project deliverables are met. Undertake these responsibilities in the project: Develop and deploy multimodal AI algorithms for fire, smoke, and hot-work detection by fusing optical, thermal/infrared, LiDAR, RADAR, and gas sensor data under varying environmental conditions. Design computer vision and human-behavior analysis models for detecting personnel, posture, casualties, and hazardous situations, including operation in low-visibility scenarios. Implement scene mapping, environment perception, and path-planning algorithms using LiDAR and RADAR data to support evacuation guidance and first-responder navigation. Build real-time predictive models for fire intensity and spread forecasting and integrate LLM-based scene description and decision support into an end-to-end deployable system. Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations. Coordinate procurement and liaison with vendors/suppliers. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Job Requirements Bachelor’s degree (minimum) in Electrical / Electronics Engineering, Computer Engineering, Computer Science, Robotics, or a closely related discipline, with foundational knowledge in signal processing and machine learning. Working knowledge of computer vision and deep learning concepts, including object detection and image-based classification, with hands-on experience using Python and at least one deep learning framework (e.g., PyTorch or TensorFlow). Basic experience handling and processing sensor data (e.g., camera, thermal, LiDAR, RADAR, or similar perception sensors) in real-world or laboratory settings. Familiarity with Linux-based development environments and standard software tools for data analysis, model training, and evaluation. Ability to independently implement, test, and document applied research solutions, with prior experience through projects, internships, or research assistantships considered sufficient. Prior experience in publishing is desirable.

At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in our education, while benefitting them with our talent supply and collaborative research achievements. The University’s unique applied learning pedagogy integrates work and study, embedding authentic learning experiences within real-world environments. Through strategic partnerships forged by our faculty with industry, learners bridge theoretical knowledge with practical application in and out of the classroom. Such active & authentic learning opportunities ensures graduates step into their careers with applicable skills and competence. In research, SIT faculty aims to bridge knowledge creation and utilisation. Our faculty collaborates closely with industry on translational research and innovation with focus on addressing pertinent industry challenges to impact businesses. The Singapore Teaching and Academic Research Talent (START) Scheme is co-funded by the Ministry of Education (MOE) and SIT to encourage and support outstanding young Singaporeans interested in pursuing an academic career at SIT. The Early Career Awards (ECA) are designed to support Singaporeans who have recently completed their postdoctoral training and prepare them for an academic career at SIT. This award aims to enhance the teaching capabilities of the recipient and help build a strong research portfolio. Eligibility and Selection Criteria Singapore Citizen  Recently completed postdoctoral training Excellent academic record plus a high degree of proficiency and motivation for a research area that is strongly aligned with SIT’s supported areas Strong passion for teaching, research and an academic career Benefits Awardees may receive research grants to help build a competitive research portfolio. Upon completion of the award, awardees will be considered for Assistant Professorship. Awardees will also be assigned a faculty mentor for the duration of the scheme. Application Process Applications are open throughout the year. Applications received before 15 January 2026 will be considered for intake 2026. Interview by the respective clusters for shortlisted applicants will be conducted throughout the year. Final Interview by Panel for shortlisted applicants will take place from March to April 2026. Awards for intake 2026 will be finalised by July 2026. Supported Areas for START Engineering Energy Resilience: Power electronic converters for distributed energy resources and microgrids; High voltage DC transmission and distribution components and systems; Electric propulsions systems for land, sea and air; Wide bandgap solid-state protective devices. Sustainable Infrastructure Engineering & Maintenance: Construction technology, Tunnel engineering, Integrated BIM for Civil and MEP design optimisation; Non-destructive testing and prognostic maintenance for infrastructure life extension. Sustainable Maritime Engineering: Ship design and optimisation towards maritime decarbonisation; maritime battery room design for safety; intelligent ship and operations; autonomous vessels and systems.