Cracow University of Technology

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.

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.

The University of Southampton in collaboration with Gham Power and Swanbarton have secured a short-term project to develop the Soluble Lead Flow Battery for installation at Gahme Power in Nepal. As a result we are seeking to appoint a fixed term 4-month research fellow to facilitate and deliver a programme of research testing aerogel thermal barrier materials within proxy and actual battery environments. You will be an mechanical engineer who holds a PhD degree or is submitting a PhD thesis before September 2026 with evidenced-supported experience of testing materials. Knowledge of electorchemcial process and physical materials properties is an advantage.  You will join a large and friendly Mechanical Engineering department and work within the Energy Technology Research Group. The project will benefit from close collaboration with other researchers and with colleagues in the collaborative project. We believe equality, diversity and inclusion are fundamental to making the University of Southampton a welcoming, vibrant and successful organisation. Having a diverse workforce, inclusive of people of all ages and beliefs, from different racial backgrounds, educational and social backgrounds opens up a wealth of possibilities, makes us more creative and accelerates our impact on society. We welcome applicants that value diversity of our community and are willing to play their part in supporting the mission of inclusivity.