K Ramakrishnan College of Engineering

Job Description 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. We are seeking a highly motivated and talented Research Fellow to join an exciting applied research project within the Infocomm Technology cluster at SIT. This project addresses the critical challenge of delivering real-time Artificial Intelligence (AI) services in Internet of Things (IoT) networks, where latency and timeliness are paramount. The successful candidate will be responsible for the end-to-end investigation of novel edge-assisted offloading strategies for IoT networks. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is to build and validate edge-assisted offloading strategies, complete with software APIs, through rigorous simulations and live demonstrations. This position is ideal for a researcher with a passion for solving complex problems at the intersection of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical, IoT systems. Key Responsibilities Participate in and manage the research project with Principal Investigator (PI) to ensure all project deliverables are met. Derivation of closed-form theoretical latency and timeliness expressions for cloud-hosted AI services and edge-assisted offloading strategies. Analysis of theoretical latency and timeliness for cloud-hosted AI services and edge-assisted offloading strategies. Design and development of edge-assisted offloading strategy and associated software APIs. Validation of edge-assisted offloading strategy via simulations and live demonstrations. Job Requirements A Ph.D degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player. Strong theoretical background in wireless communications or edge computing will be advantageous. Proven track record in research and development of edge intelligence algorithms will be advantageous. Knowledge of machine learning or reinforcement learning techniques will be advantageous. Proficiency in algorithm development using Python will be advantageous

Ref.: 534558 Work type: Full-time Department: School of Future Media (31200) Categories: Teaching Staff Applications are invited for appointments as Senior Lecturer/Lecturer in the School of Future Media (Ref.: 534558), to commence on August 1, 2026 or from as soon as possible thereafter. The appointment rank will be determined according to qualifications and experience of the successful candidate. The initial appointment will be on a two-year fixed-term basis, with the possibility of renewal subject to satisfactory performance and funding availability. Applicants should possess a Master’s degree or above in journalism, communication or related fields, with a minimum 10 years’ full-time professional and teaching experience in the journalism and media industries. Proficient knowledge of business and financial journalism is required. Knowledge and experience in Chinese Mainland, Hong Kong or Asia will be an advantage. The appointees will be responsible for teaching undergraduate and postgraduate courses in business and finance journalism, including financial reporting, corporate governance, entrepreneurship, sustainability and innovation, global business. They should also be experienced in news delivery on all platforms, and familiar with the latest digital tools in above areas. They will also take leadership roles in curriculum and course development at undergraduate and postgraduate levels, including common core courses for non-journalism or media students. Applicants with less experience may be considered for the position of Lecturer. Those who have responded to the previous advertisement (Ref: 532498) need not re-apply. A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. At current rates, salaries tax does not exceed 15% of gross income. The appointment will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totalling up to 15% of basic salary. Housing benefits will be provided for Senior Lecturer as applicable. The University only accepts online applications for the above post. Applicants should apply online and upload an up-to-date C.V. Review of applications will start as soon as possible and continue until June 30, 2026, or until the post is filled, whichever is earlier.

Industry connected research with real on farm impact Appointment flexibility at Level A or Level B Collaborative research environment with strong academic support The role Full Time, Fixed Term (until June 2030) Level A - AUD$80,046 to AUD$108,204 p.a. (plus 17% superannuation) Level B - AUD$113,841 to AUD$134,965 p.a. (plus 17% superannuation) Wagga Wagga The Gulbali Institute is seeking to appoint a Weed Scientist (either Level A or Level B) to contribute to a growing research program focused on developing, evaluating and integrating emerging weed control technologies for Australian broadacre cropping systems. Whether you are an emerging researcher or an experienced postdoctoral scientist, this is an opportunity to contribute to meaningful, industry-driven research that shapes the future of agricultural innovation. As a key member of the CSU node of the Weed Management Initiative, you will work closely with senior academics, industry partners, technology developers and research collaborators to deliver high-quality research outcomes. Depending on appointment level, you will support or lead field and glasshouse trials, data analysis, preparation of scientific outputs, and engagement with industry to bring innovative solutions into practice. About you You are a researcher passionate about agricultural innovation and ready to contribute to impactful, real world outcomes. You will bring; A PhD in weed science, agronomy, crop protection, biology, ecology. Environmental sciences or related discipline. Experience working in field and/or controlled environment research. Strong communication skills to engage academic, industry and grower audiences. Ability to work collaboratively in multidisciplinary teams. Understanding of Australian cropping systems and weed management challenges. A commitment to producing high quality research outputs that strengthen industry outcomes. A current drivers licence and willingness to travel to trial sites. About us We are a university of the land and people of our regions. True to the character of regional Australia we have gumption, we have soul and we collaborate with others. We develop holistic, far-sighted people who help their communities grow and flourish. The Wiradjuri phrase yindyamarra winhanganha means the wisdom of respectfully knowing how to live well in a world worth living in. This phrase represents who we are at Charles Sturt University - our ethos. It comes from traditional Indigenous Australian knowledge, but it also speaks to the mission of universities - to develop and spread wisdom to make the world a better place. Harnessing technology, we thrive as a distributed yet connected community, welcoming and engaging with people across Australia and the world. Learn more about the Gulbali Institute here. Visit our website to learn about our great range of employee benefits. Charles Sturt University is committed to building a diverse workforce as shown through our Athena Swan Bronze Award, our Australian Workplace Equality Index Bronze Award and our membership of a range of diversity focused organisations including Diversity Council Australia and Pride in Diversity. We encourage applications from First Nations people, carers, people from culturally and linguistically diverse backgrounds, people with disability, neurodivergent people, and people of all age groups, genders and sexualities for all roles. To apply Click the Apply button and complete your application online, and address the selection criteria in the position description and upload your CV. If you experience difficulties applying online or for further information on completing the application process please visit our how to apply page or contact us. Further information Additional information is available in the position descriptions below Position Description - Level A Position Description - Level B or by contacting: Recruitment specific enquiries: Rebecca Dwyer | Talent Acquisition Consultant | redwyer@csu.edu.au Job specific enquiries: Michael Walsh | Professor of Plant Science/ Horticulture | michwalsh@csu.edu.au Closing Date: 11pm, 28 March 2026