University of Detroit Mercy

Job Purpose 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.  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 conduct applied AI research in visual generation models, agentic AI, focusing on applications in creative content generation.  Key Responsibilities Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met. Undertake these responsibilities in the project: Conduct applied AI research in visual generation models, agentic AI. Collaborate with industry partners to develop AI solutions to address real-world problems. Develop and maintain research prototypes and software. Publish impactful research findings and present work for knowledge sharing. Work independently, as well as within a team, to ensure high-quality delivery.  Job Requirements Have relevant competence in the areas of computer vision. Have a Bachelor’s or Master’s degree in computer science, data science, AI, or related fields. Knowledge of visual generation and multimodal LLM will be advantageous. Key Competencies Proficiency in programming languages (e.g., Python and C++), and familiarity with AI frameworks (e.g., PyTorch). Self-directed learner who believes in continuous learning and development. Proficient in technical writing and presentation. Possess strong analytical and critical thinking skills. Show strong initiative and take ownership of work.

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 Applied Research Fellowship aims to provide doctoral candidates who are about to complete or have recently completed their studies an opportunity to engage in advanced training and/or research at an overseas university for one year.  Besides financial support, awardees will also receive academic mentorship.  Upon completion of the Fellowship, awardees will be considered for Assistant Professorship. Eligibility and Selection Criteria Singapore citizen  Doctoral candidates who have recently completed or are about to complete their studies in a discipline under the supported areas for START below  Excellent academic record plus a high degree of proficiency and motivation for selected research area  Have been accepted or have applied for a postdoctoral training at a leading overseas university in a research area that is aligned with SIT’s supported areas  A keen interest in an academic career Value of Fellowship The Fellowship provides  Monthly stipend  Overseas maintenance allowance  Return economy airfare  Conference and fieldwork grants  Overseas medical insurance  Fellows will also each be assigned a SIT faculty mentor throughout their post-doctoral training and have opportunities to participate in faculty development programmes.  The fellowship is tenable for one year. On an exception basis, a two-year programme may be supported. Service Commitment One year for every year of sponsorship. Application Process Applications are open throughout the year via the various links below. Applications received before 15 January 2026 will be considered for the 2026 intake.   Interview by the respective clusters for shortlisted applicants will be conducted throughout the year.   Final Interview by the Panel for shortlisted applicants for the 2026 intake will commence in Mid-March to End April 2026.   Awards will be finalised by July 2026. Supported Areas for START - Business, Communication and Design  Financial and Sustainability Accounting: The measurement, reporting, and analysis of an organisation's financial performance alongside its environmental, social, and governance (ESG) and carbon footprint. Integrating traditional financial accounting principles with sustainability considerations to provide stakeholders with a more comprehensive view of a company's long-term value creation. Meetings, Incentives, Conferences and Exhibitions (MICE): The planning, management, and execution of business events, corporate gatherings, and large-scale conferences. This field is a key segment of the tourism and hospitality industry, requiring expertise in event management, business tourism, marketing, logistics, and stakeholder engagement.

Location Abu Dhabi, United Arab Emirates Open Date Nov 14, 2025 Deadline Aug 31, 2026 at 11:59 PM Eastern Time Description MBZUAI is a research-focused university in Abu Dhabi, and the first university dedicated entirely to the advancement of science through AI. The university empowers the next generation of AI leaders, driving innovation and impactful applications of AI through world-class education and interdisciplinary research. In 2025, MBZUAI launched its first ever undergraduate program, a Bachelor of Science in AI, with two distinct streams: Business and Engineering, and are looking for passionate and highly motivated Teaching Faculty. The Undergraduate Division is seeking teaching faculty in Data Engineering and Data Science to lead a course providing the practical foundation necessary for building robust data workflows essential for modern AI, with a specific focus on Generative AI systems. This role requires delivering expert instruction on all stages of the data lifecycle, including the collection, processing, storage, and analysis of large-scale data. Key topics include data acquisition, quality assurance, statistical profiling, data mining, and the design of scalable data pipelines, with particular attention paid to the rigorous data preparation and curation required for training large generative models (like LLMs). Responsibilities include: Delivering high-quality instruction in Data Engineering, Data Science, and related AI disciplines. Developing and maintaining course content, laboratory exercises, and assessments aligned with current industry standards. Creating an engaging, application-oriented learning environment. Mentoring and advising students in course projects and applied data initiatives. Collaborating with faculty to advance teaching quality and curriculum innovation across programs. Why Join MBZUAI? Top-Tier Compensation: Competitive salaries aligned with leading global academic institutions Exceptional Benefits: Comprehensive health & life insurance Relocation support for international faculty Live in Abu Dhabi: World’s safest city, year-round sunshine, rich culture, and modern amenities Industry & Government Collaborations: Work with top AI researchers, leading tech firms, and policymakers Qualifications This position requires a Ph.D in Computer Science, Data Science, Artificial Intelligence, Information Systems, or a related field. Demonstrated expertise in Data Engineering, Data Management, and Data Analytics. Experience with relevant tools and platforms (e.g., SQL, Python, Spark, Hadoop, cloud-based data systems). Strong commitment to teaching excellence and experiential learning. Teaching Experience: Proven teaching or training experience at the undergraduate or graduate level (or equivalent professional training experience) Application Instructions To apply for this position, please submit the following: Cover letter Curriculum Vitae Teaching statement Reference letters or Name and contact details for three referees *MBZUAI's mission includes fostering a diverse academic community. MBZUAI is an equal opportunity employer. The university actively recruits faculty from around the world, aiming to create an international and inclusive environment that reflects a wide range of cultures and perspectives. *Be part of AI’s future—apply today to MBZUAI! *#MBZUAI #careeropportunities #AI