Japan Advanced Institute of Science and Technology (JAIST)

Ref.: 534618 Work type: Full-time Department: Department of Physics (25600) Categories: Senior Research Staff & Post-doctoral Fellow Post-doctoral Fellow in High-Energy Astrophysics in the Department of Physics Applications are invited for appointment as Post-doctoral Fellow in High-Energy Astrophysics in the Department of Physics (Ref.: 534618), to commence as soon as possible for two years, with the possibility of renewal subject to funding availability and satisfactory performance. Applicants should possess a Ph.D. degree in Physics or Astronomy. The appointee will work with Prof. Stephen C.Y. Ng to pursue research in areas related to neutron stars, pulsar wind nebulae, or supernova remnants. Applicants with experience analysing radio interferometer data are especially encouraged to apply. A highly competitive salary commensurate with qualifications and experience will be offered. Other benefits include annual leave, medical benefits, and free access to on-campus gyms and libraries. At current rates, salaries tax does not exceed 15% of gross income. The University only accepts online application for the above post. Applicants should apply online and upload an up-to-date C.V. (including a publication list), a cover letter, and a research statement. Applicants should also arrange three reference letters to be sent to Prof. Stephen Ng by e-mail (stephen_ng@hku.hk) directly. Review of applications will start as soon as possible and continue until April 15, 2026, or until the post is filled, whichever is earlier. The University is an equal opportunities employer and is committed to equality, ethics, inclusivity, diversity and transparency

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 Food, Chemical and Biotechnology Sustainable and Functional food: Sustainable food systems & circular food economy - alternative proteins, upcycled ingredients); AI & automation in food manufacturing - smart sensors, digital twins, and AI-driven food quality control and processing; Food safety - supply chain tracking/monitoring, blockchain Biotechnology: Host strain screening and engineering for microbial bioprocess development; microbial physiology and adaptation for industrial applications; high-throughput screening and automation for strain optimization; bioprospecting for novel microbial hosts, enzymes, and metabolites to support sustainable biomanufacturing. (Bio)pharmaceuticals: Processing science and technology for bio- and chemical transformations, separations, purifications and formulation applied to pharmaceuticals manufacture; modelling of processing steps and whole processes to support innovation, design, optimisation and control for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital twins and real-time process monitoring and control; process analytical technology (PAT); process intensification and sustainability.