Salem University

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.

Description The Modern Compilers Lab in the Computer Science program at New York University Abu Dhabi, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon are building new specialized programming frameworks. This is because these companies need to allow their users to write simple, high-level code and run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures without changing the code. Our research team at NYUAD (New York University Abu Dhabi) is developing a new programming framework called Tiramisu [1]. Unlike existing frameworks, Tiramisu can perform advanced code optimizations that are hard to apply otherwise. Because of this, Tiramisu can generate fast code that outperforms highly optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations in parallel), enhancing data locality by fusion, and blocking (i.e. accessing arrays in a way that improves temporal and spatial data locality). A large number of optimizations exist and choosing which optimization should be used and which should not is important for performance. In some situations, some optimizations are harmful to performance while they are beneficial in other situations. Currently, there is no way to help users choose which optimizations should be used. Expert programmers usually spend a lot of time trying different optimizations manually to find the best set of optimizations. The goal of this project is to add support for automatic code optimization in Tiramisu. In particular, we want to use machine learning/deep learning to achieve this. Currently, a basic automatic optimization module that relies on machine learning has been developed and we want to take that module to the next level. The final product of this project would be a compiler pass that allows Tiramisu to automatically choose which optimization should be used for a given unoptimized program. We want to produce a high-quality technique that can be used by the users of Tiramisu and especially by our partner companies and research labs. Candidates must hold a bachelor’s degree or equivalent in Computer Science, though a master’s degree is preferred. The ideal candidate will have Internship or experience in the areas of compilers and artificial intelligence. For consideration, applicants need to submit a cover letter, curriculum vitae, transcript, statement of research interests and two letters of reference, all in PDF format. If you have any questions, please email Prof. Riyadh Baghdadi at baghdadi@nyu.edu or mrasras@nyu.edu. The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled. About NYU Abu Dhabi https://nyuad.nyu.edu/en/ NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity’s shared challenges. NYU Abu Dhabi’s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents. NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching. UAE Nationals are encouraged to apply. References [1] http://tiramisu-compiler.org/

As a University of Applied Learning, Singapore Institute of Technology (SIT) works closely with industry partners to develop applied research capabilities that translate directly into real-world deployment. Our research staff are equipped with industry-relevant skills through hands-on work on operational research platforms and systems. The Future Ship and System Design (FSSD) programme aims to develop strategic and innovative design capabilities for the maritime industry in Singapore and globally. We are seeking a certified Power Electrical Engineer to design, analyse, and operate high-power and high-voltage electrical systems, ensuring safe, reliable, and compliant operation across our facilities. The candicate will work closely with the Principal Investigator (PI), Co-PI, and research team members to manage and execute the project, ensuring that all deliverables are successfully achieved. Key Competencies Design and review high-power electrical systems, including switchgear, transformers, generators, and protection schemes Perform power system studies such as load flow, short-circuit, and protection coordination Operate and control high-power or high-voltage equipment Lead testing, commissioning, and troubleshooting of electrical systems Ensure compliance with electrical safety rules, standards, and regulatory requirements Support maintenance planning, reliability improvement, and asset management Work independently, as well as within a team, to ensure proper operation and maintenance of equipment The employee is to communicate with any relevant internal or external stakeholders to ensure project deliverables are met. Any other adhoc duties assigned by supervisor. Job Requirements Bachelor’s degree in Electrical Engineering or equivalent Certification or authorisation to design and operate high-power or high-voltage electrical systems Minimum 2 years of relevant experience Key Competencies Good knowledge in electrical equipment and power system design. Good knowledge in reliability analysis. Strong knowledge of HV and LV power systems and protection Experience with power system analysis tools Strong safety mindset and clear technical communication skills