Nahda University in Beni-Suef

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.

Ref.: 534824 Work type: Full-time Department: Department of Paediatrics and Adolescent Medicine, School of Clinical Medicine (21100) Categories: Professoriate Staff Applications are invited for the appointment as Tenure-Track Associate Professor/ Assistant Professor in the Department of Paediatrics and Adolescent Medicine, School of Clinical Medicine (Ref.: 534824), to commence as soon as possible, on a three-year fixed-term basis, with the possibility of renewal subject to satisfactory performance and consideration for tenure before the expiry of a second three-year fixed-term contract. Exceptionally outstanding candidates for the position of Associate Professor may be considered for appointment on tenure terms, subject to University’s approval. Applicants should possess: (i) a Ph.D. degree or equivalent in a related discipline; (ii) a strong track record of high-quality research as indicated by publication record and external grants; (iii) evidence of international recognition; (iv) a strong record of scholarship with a demonstrated ability to work across disciplines towards new research initiatives; and (v) a strong commitment to engaging students in inquiry-based learning at both undergraduate and postgraduate levels.  Expertise in bioinformatics, high-throughput sequencing data analysis, and computational biology is essential. Skills in applying data science and artificial intelligence to biomedical problems are highly valued. Familiarity with statistical modeling, data mining, and pipeline development for genomics and neurodevelopmental research will enhance a candidate’s profile. The appointee is expected to conduct independent and collaborative scholarly research and attract competitive grants to maintain active research programmes; take part in teaching undergraduate and postgraduate programmes, and supervise research postgraduate students; and perform administrative duties. The appointment rank will be determined based on the qualifications and experience of the successful candidate. If the candidate’s research output, experience, and qualifications are of higher caliber, they may be considered for an Associate Professor position, reflecting their seniority and leadership in the field. Additional information about the Department is available at https://paed.hku.hk/en1/. 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, totaling up to 15% of basic salary. Housing benefits will also be provided as applicable. The University only accepts online applications for the above post. Applicants should apply online at the University's career site (http://jobs.hku.hk), and provide a cover letter, curriculum vitae, research statement, teaching statement, 2 or 3 most significant research publications, and contact information for at least three referees. Review of applications will start on May 28, 2026 and continue until October 5, 2026, or until the post is filled, whichever is earlier.

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