University of Bridgeport

Lingnan University is one of the eight publicly funded institutions in the Hong Kong Special Administrative Region (HKSAR) and has the longest established tradition among the local institutions of higher education. It is widely recognised for providing quality education with a focus on whole-person development and conducting high-impact research for a better world. Moving forward, Lingnan University is well positioned to take lead as a comprehensive university in arts and sciences in the digital era, with impactful research and innovations. Lingnan University offers undergraduate, taught postgraduate, and research postgraduate programmes in the Faculties of Arts, Business, Social Sciences, and the Schools of Data Science, Graduate Studies and Interdisciplinary Studies. To foster interdisciplinary collaboration and scientific progress, Lingnan University established the Lingnan University Institute for Advanced Study (LUIAS), attracting distinguished scholars from around the world to collaborate with its faculty and students. With traditional strengths in arts, business, social sciences, and interdisciplinary studies, the University aims to equip students with practical knowledge and critical thinking skills to thrive in the future. Subsequent to the establishment of the School of Data Science and LUIAS, Lingnan University is transforming into a hub for global leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/. Applications are now invited for the following post: Chair Professor Department of Accountancy (Post Ref.: 25/208) The Department is looking for a Chair Professor to provide strong academic leadership in both research and teaching, and to contribute to the administration and management of the Department of Accountancy, and to the development of the Faculty of Business. It is expected that the appointee can contribute to AI, data science and STEM-related accounting research in alignment with the University’s strategy and to significant leadership service. General Requirements Candidates should have (a) a PhD degree in a relevant discipline with substantial teaching experience; (b) a strong international reputation and an outstanding track record of high impact research publications and competitive research grants; (c) strong research leadership capabilities and experience, with a commitment to helping other faculty develop their research and providing research supervision to students; and (d) previous administrative leadership experience at the Department or Faculty level will be a distinct advantage. Lingnan University is fully committed to the pursuit of excellence in both teaching and research. Candidates are required to provide evidence of quality teaching and information on their research records. The appointee is expected to have a strong commitment to teaching excellence and services to the Department, the University community, and to engage actively in quality research and publication. Appointment Internationally competitive start-up packages are available for the successful candidate. A globally competitive remuneration package commensurate with the appointee’s qualifications and experience will be offered. Fringe benefits include annual leave, medical and dental benefits, mandatory provident fund (retirement benefits scheme), gratuity, and incoming passage and baggage allowance for the eligible appointee. Appointment with substantiation/tenure will normally be considered. Application Procedure (online application only) Please click "Apply Now" to submit your application. Applicants shall provide names and contact information of at least three referees to whom applicants’ consent has been given for their providing references. Personal data collected will be used for recruitment purposes only. We are an equal opportunities employer. Review of applications will continue until the post is filled. Qualified candidates are advised to submit their applications early for consideration. The University reserves the right not to make an appointment for the post advertised, or to fill the post by invitation or by search. We regret that only shortlisted candidates will be notified.

Role type: Full-time; Continuing Faculty: Science Department/School: School of Mathematics and StatisticsSalary: Level of appointment is subject to qualification and experience Level B: AUD $124,656 -$148,023 p.a. Level C: AUD $152,695 -$176,065 p.a. Level D: AUD $183,859 - $202,556 p.a. plus 17% super(retirement savings system/pension scheme)Develop innovative statistical methods for complex 'omics datasets.Apply now to join a world-class school in a leading University.Investing in you - benefits package including salary packaging, health and wellbeing programs, discounted services, and professional development opportunities. The University of MelbourneWe take pride in our people, who all contribute to our mission to benefit society through the transformative impact of education and research. The University of Melbourne provides an outstanding environment in which to develop innovative research in mathematical and statistical data science, with opportunities for collaborations with machine learning and bioinformatics researchers in Computing and Information Systems, biostatisticians in Population and Global Health, big data research in genomics in the Melbourne Integrative Genomics research hub, optimisation researchers in the ARC Training Centre OPTIMA, biological systems modelling or quantum biotechnologies in the ARC Centres MACSYS and QUBIC, as well as applied and theoretical approaches to data science in other departments/faculties across the University.Your next career opportunityThe School of Mathematics and Statistics invites applications for a Lecturer/Senior Lecturer, or Associate Professor from dynamic individuals at the forefront of 'omics technologies. The appointment will be at Level B, C, or D (Lecturer, Senior Lecturer, or Associate Professor), depending on the candidate's previous experience. The research will develop and apply statistical methods to complex 'omics data such as genomics, transcriptomics, and microbiome data, with encouragement for work in statistical machine learning. We seek a candidate whose profile complements the School's strengths in data science, including mathematics, statistics, machine learning, optimisation, biostatistics, and genomics. A strong commitment to high-quality teaching and supervision of undergraduate, MSc, and PhD research students is essential. You will be affiliated with Melbourne Integrative Genomics (MIG), a University initiative focused on pioneering statistical methods for omics data. Your responsibilities will include: Conduct Innovative Research: Lead a research programme in statistical genomics, publish in high-impact journals, and secure external funding.Deliver High-Quality Education: Develop and teach statistics and data science courses at undergraduate and postgraduate levels.Supervise Research Students: Guide MSc and PhD students in their research projects, fostering the next generation of data scientists.Engage in Interdisciplinary Collaboration: Work with researchers across the university on cutting-edge projects in bioinformatics and machine learning.You may be a great fit if: You have a strong statistics background and expertise in computational biology to establish and lead a high-level research program. You may also: Hold a PhD in statistics or a closely related discipline.Have a strong publication record in statistical learning applied to large biological datasets.Demonstrate the ability to secure research funding through competitive grant schemes.Possess excellent teaching skills and the ability to develop curriculum in data science.Have experience in supervising graduate students and fostering their academic growth.For further information please refer to the attached PD. What we offer you!We offer the opportunity to be part of a vibrant community and enjoy a comprehensive range of benefits to support your success and sense of fulfillment, including: Supportive flexible work arrangements underpinned by our commitment to inclusion and well-being Progressive, considerate leave provisions to empower your work-life balance Salary packaging and access to a range of discounted services including Bupa health insurance Health and well-being services including a leading Employee Assistance Program For more information check out our benefits page!Your new team - "School of Mathematics and Statistics"The University of Melbourne's School of Mathematics and Statistics is one of Australia's leading mathematics and statistics schools. It has achieved this status through the high quality of its research and teaching programs. The School offers a wide range of subjects to undergraduate and postgraduate students and is involved in aspects of community life that impact on the interests of the School and the discipline. The School of Mathematics and Statistics has a total of 90 continuing teaching and/or research staff; 37 research only staff and consultants; 19 academic specialists and 16 support staff. In 2023, there were 143 Research Higher Degree and 189 Coursework Master of Science students.The School has had 10 staff members inducted as Fellows of the Academy of Science. Be YourselfThe University of Melbourne is an Equal Opportunity Employer and a child-safe organisation. We are committed to creating an inclusive and equitable workplace where all individuals feel valued, respected, and have the opportunity to thrive regardless of gender identity, ethnicity, sexual orientation, disability, age, being a parent or having caring responsibilities.The University of Melbourne is committed to fostering a barrier-free and inclusive recruitment process. We are dedicated to providing reasonable adjustments for candidates throughout the application and interview stages, including accessible document formats and alternative application methods.To discuss your specific requirements, please feel free to contact Bec Tucker - 0416 888 299 or send an email titled 'Reasonable Adjustments' to hr-careers@unimelb.edu.au.You can find more information for applicants requiring reasonable adjustments on our Careers website: https://about.unimelb.edu.au/careers Aboriginal and Torres Strait Islander ApplicantsWe aspire to be the University of choice for Indigenous Australians, with unprecedented investment to attract, nurture and retain Aboriginal and Torres Strait Islander students and staff. Tangible support through a range of programs and initiatives will ensure that you personally succeed and flourish while at the University of Melbourne. For further information, including our 2023-2027 Indigenous strategy please visit -https://about.unimelb.edu.au/reconciliation/murmuk-djerringIf you are a member of an Aboriginal and/or Torres Strait Islander community and would like any support, please feel free to contact our Indigenous Employment & Development team via email at oied-hr@unimelb.edu.au.Working at the University - what you need to knowThis role requires the successful candidate to maintain a Working with Children Check The successful candidate can apply for the WWCC as part of the onboarding process. In the case the selected candidate doesn't have a valid Working with Children Check, they will be able to apply for the WWCC as part of the initial onboarding procedures.Please note: Visa sponsorship is available for this position. Join Us and unlock your career potential!Is this the perfect opportunity for you? Apply today! Including the following documents: Resume Cover Letter outlining your interest and experience The responses against the Selection Criteria^ (found in the Position Description) ^For information to help you with compiling short statements to answer the selection criteria and competencies, please go to http://about.unimelb.edu.au/careers/selection-criteriaIf you have any questions regarding the recruitment process, please feel free to contact Anna Gradoboeva via email at hr-careers@unimelb.edu.au, ensuring that you include the Position Number and the Job Title as the subject. Please do not share your application to this email address.If you have any particular questions regarding the job please follow the details listed on the Position Description.Applications close: 2 February 2026, 11:00 PM / Melbourne time zone.Position Description:JR-001551 Lecturer Senior Lecturer Associate Professor in Statistics for Omics_PD.pdf

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 support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI, and research team to ensure timely achievement of project deliverables. Undertake the following specific responsibilities in the project: i. Develop, train, and optimise deep learning models for object detection, classification, and segmentation using real-world datasets. ii. Design and implement software modules to integrate the models into a working system prototype. iii. Perform data annotation. iv. Conduct experiments, analyse results, and iterate models for improved accuracy and efficiency. v. Prepare project documentation, technical reports, and academic publications. vi. Collaborate with industry partners and contribute to technology transfer efforts. Job Requirements 1. Possess strong technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models 2. Hold at least a Bachelor’s degree in Computer Science, Electrical/Electronic/Software Engineering, or a related field. A Master’s or PhD degree in relevant areas will be advantageous. 3. Familiarity with the following areas is advantageous: Participation in Kaggle competitions, showcasing practical problem-solving and model development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D projects Key Competencies Able to build and maintain strong working relationships with team members, stakeholders, and external partners Self-motivated and committed to continuous learning and improvement Proficient in technical writing & presentation, research reporting, and academic publication Possess strong analytical, problem-solving, and critical thinking skills Demonstrate initiative and ownership in carrying out tasks independently