MIOTI Tech and Business School

Schemes of Service: Faculty Division: Food, Chemical and Biotechnology Employment Type: Fixed Term As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. Job Responsibilities Participate in and manage a few research projects with the Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met. Accumulate data from Co-PIs for quarterly, annual, or final progress reports• Schedule meetings with co-PIs, collaborators on-site or off-site Update research or project team's activities on social media, website, and record videos when needed. Supporting PI/research team for overseas traveling, meetings, budgeting and collecting photos for reports. Facilitate visiting students or scholars for internal document collection and approval. Collect documents needed for different projects as KPIs. Undertake these responsibilities in the project: i. Lead and support high-quality publications to disseminate the applied research outcomes. ii. Plan, organize, and carry out experiments and trials in the labs to achieve the objectives iii. Manage and complete the project by presenting the findings in conferences or meetings with industrial collaborator, submitting timely data & documents, and purchasing chemicals or consumables. iv. Consolidate the data in order to generate sufficient scientific evidence for meeting slides and reports. v. Engage and communicate with collaborators for progress meetings and report generation to meet the grantor's requirements. The candidate is to liaise and communicate with any internal or external stakeholders to ensure project deliverables are met and to perform any other adhoc duties assigned by Supervisor.  Job requirements Have relevant competence in the areas of project management, organizing documents, and facilitating report drafting. Have a degree in Food Science and Technology, Engineering or Science is a bonus. Some analytical work experience for texture analysis, food formulation and characterization, or publication is a bonus Detail-oriented person, able to communicate with industrial collaborators to share key findings, seek supports, or conduct commercial trials. Coordinate procurement and liaison with vendors/suppliers. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.

Schemes of Service: Faculty Division: Infocomm Technology Employment Type: Permanent, Fixed Term The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry‑relevant degree programmes that prepare graduates to be work‑ and future‑ready professionals. SIT’s mission is to maximise the potential of its learners and to innovate with industry through an integrated applied learning and research approach. Our distinctive pedagogy integrates work and study, emphasising authentic, real‑world learning through close collaborations with strategic industry partners. SIT’s centralised campus in the Punggol Digital District, together with strategically deployed “Living Labs,” provides a tightly integrated ecosystem where academia, industry, and community converge.     SIT is expanding its applied AI research capabilities, building a cohort of AI faculty who are keen and experienced working on industry problems across sectors. We are recruiting faculty candidates at all levels of seniority. Responsibilities: Lead and contribute to applied research projects with industry partners and government agencies in one or more of the following AI application areas: Advanced Manufacturing & Semiconductors Urban Systems AI-Augmented Engineering AI Safety & Security Chemical Engineering & Biotechnology Healthcare Hospitality & Tourism Develop and teach applied AI courses within the cluster’s programmes and across relevant interdisciplinary modules. Supervise Industry Doctorate/Masters and capstone projects in collaboration with domain faculty and industry partners. Contribute to SIT’s continuing education offerings. Serve as AI mentor for existing SIT domain faculty through joint projects and co-supervision mechanisms. Qualifications: PhD in Computer Science, Engineering, or a relevant domain with demonstrated AI/ML research experience. Equivalent industry experience may also be considered. Technical expertise and deep knowledge of one or more of the following areas: Physics-informed neural networks (PINNs) & surrogate modelling Time-series modelling & anomaly detection Bayesian methods & uncertainty quantification LLMs & multi-modal models Graph neural networks (GNNs) Reinforcement learning Edge AI & model optimisation Trustworthy AI (explainability, auditability, privacy) Spatiotemporal data engineering Digital twins & simulation Experience applying AI to the SIT’s focus areas Demonstrated leadership and evidence of working on industry/society-defined problems Experience with industry research collaborations, applied research grants, and/or system deployment Established thought leadership and/or professional standing e.g. publications in top journals and keynotes Non-publication outputs and impact such as open-source tools, technical reports, patents, deployed systems Track record of cross-disciplinary collaborations Strong supervisory and mentoring skills, with an interest in working closely with students in an educational environment. Ability to communicate clearly with domain experts, industry practitioners and the general public What SIT offers: An applied research environment to tackle real-world problems together with industry partners Opportunities to shape a coherent applied AI research agenda with colleagues across disciplines and build Singapore’s applied AI research capability at a pivotal moment Access to SIT’s Living Lab Network and Punggol Digital District ecosystem as testbeds SIT values applied research impact and evaluates faculty according to how their research makes a difference to society or industry Singapore’s exceptional quality of life, competitive personal tax environment, and position as Asia’s leading research and innovation hub How to apply: Candidates should submit the following: Curriculum vitae including grants, publications, and non-publication outputs (code, datasets, patents, technical disclosures) Cover Letter Research statement (up to 3 pages) addressing your applied AI research programme, how it connects to SIT’s cluster context, and your experience with industry-connected research. Highlight three past research outputs with a brief explanation of each output’s impact. Teaching statement (up to 1 page) addressing your approach to applied learning

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/