University of Liège

Job Title: Lecturer (Early Career Faculty)/ Assistant Professor/ Associate Professor in IT & AI Job Level: Level A/ B/ C Location: Gurugram, Delhi NCR. Employment Type: Full-Time About Victoria University Victoria University (VU) is a leading dual-sector tertiary institution based in Melbourne, Australia, offering both higher education and TAFE programs. With over 42,000 students globally, including a strong international presence, VU operates across multiple campuses in Melbourne, Sydney, and partner institutions in Asia (Sri Lanka and China). Guided by its strategic plan “Start Well, Finish Brilliantly 2022–2028”, the University aims to become a global leader in dual-sector learning and impactful research. VU is known for its industry partnerships, innovative teaching models, and commitment to creating career-ready graduates while fostering inclusive and future-focused education. In India, Victoria University (VU) is establishing its first India campus in Gurugram, Delhi NCR, scheduled to open in mid-2026, delivering industry-aligned programs with a global curriculum. The Gurugram campus focuses on emerging technologies such as Artificial Intelligence, Data Science, and Information Technology, providing students with international exposure, practical learning, and strong industry connections. Position Summary The Lecturer (Early Career Faculty)/ Assistant Professor/ Associate Professor in IT & AI (Level A/B/C) will play a pivotal role in advancing teaching, research, and curriculum innovation within the Information Technology Program under the College of Arts, Business, Law, Education and IT. This position focuses on integrating Generative AI (GenAI) and Large Language Models (LLMs) into teaching, research, and industry engagement. The successful candidate will contribute to program growth by modernising courses, increasing student enrolments, and strengthening expertise in AI, cybersecurity, data science, and ICT management. Indicative Areas of Expertise Artificial Intelligence & Generative AI (LLMs, RAG, copilots) Cybersecurity & Network Management Data Science & Analytics Cloud & Mobile Application Development Software Development & UI/UX ICT & Project Management Key Responsibilities 1. Teaching & Coordination Deliver and coordinate IT units across onshore and transnational campuses (Sydney, Brisbane, Sri Lanka, China). Integrate GenAI tools (LLM APIs, RAG systems, copilots like Claude Code/OpenAI Codex) into at least two units annually. Design assessments, ensure marking consistency, and maintain academic standards. 2. Curriculum Innovation & Student Experience Lead course modernisation using GenAI-driven teaching methodologies (flipped, hybrid, online). Continuously update curriculum aligned with industry trends and emerging technologies. Enhance student engagement and support enrolment growth initiatives. 3. Research & Scholarship Conduct applied research in LLMs, AI, and related domains. Publish high-quality research (minimum one Q1 or CORE A* paper annually). Develop demonstrable AI systems for lab use and online showcases. 4. Supervision & Mentoring Design innovative honours, master’s, and capstone projects involving GenAI applications. Supervise undergraduate and postgraduate research students. 5. Service & Industry Engagement Contribute to research grant proposals and industry collaborations. Participate in academic administration, quality assurance, and compliance activities. Engage with industry partners and maintain cross-cultural collaboration.   Qualifications & Selection Criteria Essential Assistant Professor: PhD (or equivalent) in Information Technology, Artificial Intelligence, or a related discipline. Lecturer (Early Career Faculty): Master’s degree and/or currently a PhD candidate in Information Technology, Artificial Intelligence, or a related discipline. Relevant teaching experience Demonstrated expertise in GenAI/LLMs (API integration, RAG, copilots). Strong teaching capability across IT domains. Proven research track record (Q1 / CORE A* publications). Experience in curriculum development and GenAI integration. Ability to design real-world AI-driven systems. Strong communication, organisational, and interpersonal skills. Commitment to professional standards, ethics, and university policies Desirable Experience securing competitive research funding. Application Requirements Applicants are required to submit with the following documents: Resume (Curriculum Vitae) Cover Letter If you experience any issues while submitting your application, please email: career@daskalos.com

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 Purpose The primary responsibility of this role is to deliver on an academic research project funded by BCA. The project is in collaboration with IHL and an industry partner. where you will be part of the research team to develop and demonstrate Building-to-Grid Integration through Intelligent Optimization and Predictive Control at SIT’s Punggol campus. Under this job title, you will be required to establish a test bed in SIT’s Punggol campus building, benchmarking of current building energy performances, deployment of new sensors & hardware, and quantitative evaluation of energy savings. You will be required to coordinate with multiple internal and external parties for the successful deployment of technology, test-bedding, and energy performance evaluation. Key Responsibilities Participate in and manage the research project with the Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met. Candidate will be required to establish test bed in SIT’s Punggol campus building, benchmarking of current building energy performances, deployment of new sensors, hardware, quantitative evaluation of energy savings, etc. Meeting the deliverables by deployment, demonstration, and experimental studies planned for under the scope of work of the projects within the timeframe to meet the deliverables. Coordination with project internal and external team members, vendors, contractors, safety officers, for successful deployment of technology and testing. Assists in the co-supervision of final year projects (FYP) or capstone projects students under the Project PI. Assists the PI in drafting project reports, conference proceedings, and journal articles based on the outcome of the projects. Prepares and shares a fortnightly report of results from the computations with the PI. Carry out Risk Assessment, and ensure compliance with Work, Safety, and Health Regulations. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Job Requirements PhD degree in electrical/civil/mechanical engineering or other related fields Expert knowledge of building air-conditioning and mechanical ventilation, simulation, building automation and control, sensor network, thermal energy storage, indoor air quality, heat transfer, and building energy performance evaluation.  Experience of test bed setup development, testing & commissioning, and performance analysis. Knowledge of industrial protocols, sensors, and control hardware. Knowledge of building management systems, software integration, data collection, and analysis. Industry or research lab experience is required. Strong analytical and conceptual abilities. Ability to work in a team as well as independently. Able to work under pressure and meet deadlines. Key Competencies  Able to build and maintain strong working relationships with people within and external to the university. Able to work independently with strong data analytical skills, communication and interpersonal skills. 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

Role Overview We are looking for a motivated Material Science and Engineering Engineer to join our team. In this role, you will lead the development and testing of materials for various applications, contributing to innovative projects that drive our mission forward. This involves researching, developing, testing, and processing materials like metals, plastics, and ceramics to improve product performance. You will lead and apply best practices in materials science and engineering. Key responsibilities include analysing material structures at the atomic level, conducting failure analysis, selecting materials for new products, and optimizing manufacturing processes Responsibilities R&D: Lead material selection, development, and characterization for applications in electronics, aerospace, or biomedical devices; evaluate and integrate new analytical instrumentation. Testing & Characterization: Design and execute experiments to evaluate mechanical, thermal, and chemical properties; analyze data to inform design decisions. Failure Analysis: Root-cause investigation of material failures; recommend and validate corrective actions. Process Development: Optimize manufacturing processes (e.g., casting, coating); qualify and collaborate with suppliers with minimal supervision. Collaboration & Communication: Partner with design, manufacturing, and supply chain teams; deliver clear technical reports and presentations. Sustainability & Compliance: Assess environmental impact of materials; maintain lab safety and regulatory compliance. Required and Preferred Qualifications Bachelor's in Materials Science/Engineering or related field + 2+ years of experience in materials R&D or product development. Hands-on experience with materials characterization (e.g., SEM, XRD, FTIR, mechanical testing). Proficiency in data analysis tools (Python, MATLAB, JMP) and technical documentation. Strong analytical skills and attention to detail. Excellent written and verbal communication skills. Resourceful, meticulous and problem-solving attitude. Technical Skills and Relevant Technologies: Experience with CAD/CAE tools (SolidWorks, ANSYS) and DFM/DFA principles. Knowledge of industry standards (ASTM, ISO) and regulatory frameworks (e.g., ISO 13485 for biomedical). Characterization: SEM/EDS, XRD, DSC/TGA, tensile/impact testing. Software: Thermo-Calc, Materials Studio, Python/R for data analysis, CAD (SolidWorks). Processes: Experience with additive manufacturing, thin-film deposition, or polymer processing. Standards: Familiarity with ASTM, ISO, or industry-specific material specifications.