I.K. Gujral Punjab Technical University

Ref.: 536223 Work type: Full-time Department: HKU Institute for Climate and Carbon Neutrality (47100) Categories: Senior Research Staff & Post-doctoral Fellow Post-doctoral Fellow in the HKU Institute for Climate and Carbon Neutrality (Ref.: 536223)  We now invite applications for the captioned post. Duties and Responsibilities The appointee will work closely with the Supervisor and the core research team. The main duties include: Leading and contributing to a targeted research project, topics including climate policy, economics and governance. Designing, developing, and continually refining robust research instruments and methodologies. Coordinating comprehensive data collection processes and executing rigorous data analysis. Supporting the planning, organization, and execution of academic and public dissemination events, such as seminars, workshops, and conferences. Assisting in drafting high-quality academic papers, policy briefs, and project progress reports. Performing other research and administrative duties as assigned to support the Institute's objectives. Requirements A Ph.D. degree in Environmental Economics, Public Policy, Geographical Sciences or a highly related discipline. A minimum of one year of relevant post-doctoral or professional working experience in a related field. An excellent command of both written and spoken English. Strong interpersonal, communication, organizational, and problem-solving skills. A demonstrated ability to work efficiently under pressure, manage multiple priorities, and meet tight project deadlines. A strong capacity to work both independently and collaboratively within a diverse academic and administrative team. A highly self-motivated, proactive, and responsible work ethic. Advantageous: Familiarity with the local funding system, alongside prior experience collaborating with schools or managing educational/environmental research projects. Preferred: Proficiency in analyzing complex quantitative research data using advanced statistical methods and software packages. What We Offer The appointment will commence as soon as possible on a temporary basis for 1 year, with the possibility of renewal subject to satisfactory performance and funding availability. A highly competitive salary commensurate with qualifications and experience will be offered. Other benefits include annual leave, medical benefits and free access to on-campus gyms and libraries. How to Apply The University only accepts online application for the above post(s). Applicants should apply online at the University’s Careers site (https://jobs.hku.hk) and upload an up-to-date C.V. Review of applications will start as soon as possible and continue until [31 August, 2026], or until the post is filled, whichever is earlier. The University is an equal opportunities employer and is committed to equality, ethics, inclusivity, diversity and transparency

We are looking for a Research Engineer to join our MOE AcRF Tier 1 funded research project at the Singapore Institute of Technology. You will be part of an interdisciplinary team spanning accounting and NLP/AI, working to design, build, and validate a pipeline that detects inconsistencies and contradictions between firms' written financial filings (10-K/10-Q) and spoken earnings call transcripts. The role involves implementing retrieval-augmented natural language inference models and LLMs, processing large-scale financial text data, and supporting empirical analysis of contradiction scores.  Job Responsibilities Drive the technical execution of the research project under the guidance of the PI and Co-PI, ensuring project deliverables and timelines are met. Design and implement the retrieval-augmented NLI pipeline for inconsistency and contradiction detection across corporate disclosures (earnings call transcripts and SEC filings). Perform large-scale text preprocessing, cleaning, segmentation, and indexing of earnings call transcripts and financial filing corpora. Implement claims extraction modules using LLM-based approaches to identify key assertions from corporate disclosures. Build semantic retrieval mechanisms (e.g., Sentence-BERT embedding similarity search) for matching claim-context pairs across disclosure channels. Implement and evaluate contradiction detection models using NLI frameworks and LLM prompting techniques. Aggregate model outputs into firm-quarter level scores and prepare structured datasets for empirical analysis. Support human-in-the-loop validation by coordinating with student annotators and preparing annotation guidelines. Maintain reproducible research workflows using version control (Git) and systematic documentation of processes, code, and findings. Job Requirements Bachelor’s degree or Master’s degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, or a closely related field. Strong programming skills in Python, with experience in relevant libraries such as HuggingFace Transformers, PyTorch/TensorFlow, and scikit-learn. Prior experience or coursework in natural language processing, machine learning, or information retrieval. Familiarity with version control tools (e.g., Git/GitHub) and collaborative development practices. Experience with financial data or financial text analysis will be advantageous. Familiarity with LLM APIs, prompt engineering, and retrieval-augmented generation (RAG) workflows will be advantageous. Good communication skills and ability to work both independently and collaboratively.

Ref.: 536252 Work type: Full-time Department: Faculty of Social Sciences (30000) Categories: Professoriate Staff Applications are invited for appointment as Professor / Associate Professor in Demography / Population Studies in the Department of Sociology (Ref.: 536252), to commence on January 1, 2027, or as soon as possible thereafter. Exceptionally outstanding candidates may be considered for appointment on direct tenure terms subject to the University’s approval. The successful candidate may entrust with leadership roles in the recently established HKU Research Hub of Population Studies. Applicants should possess a Ph.D. degree in Demography or Sociology, and demonstrate a strong commitment to excellence in teaching, research, and academic leadership. Candidates should have a strong scholarly track record, including high-quality research and publications in leading academic journals, and demonstrate the ability to contribute to the Department’s research and teaching in population-related areas. The Department is particularly interested in applicants with expertise in areas such as low fertility societies, family and life-course dynamics, migration, health and mortality, and computational, digital or AI-related approaches to population research. We welcome applicants with diverse theoretical and methodological approaches, preferably with an Asian focus. The University of Hong Kong Founded in 1911, the University of Hong Kong has attained its pre-eminence as a research-led comprehensive university through upholding the highest international standards of excellence in its research pursuits, scholarship, teaching and learning, and service to the community. The University is consistently ranked amongst the world’s top universities: 11th in the QS World University Rankings 2026, 1st in the QS Asia University Rankings 2026, 33rd in the Times Higher Education World University Rankings 2026, and is recognised as the 4th most international university in 2025. More information about HKU can be found at https://hku.hk/. Department of Sociology The Department of Sociology at HKU is the first sociology department in Hong Kong. The Department was ranked 24th in the world in Sociology in the 2026 QS World University Rankings. The Department offers a range of innovative and engaging taught programmes, including undergraduate major/minor programmes in Sociology, Criminology, and Media & Cultural Studies. In addition to research postgraduate degrees, it also offers three taught postgraduate programmes in Sociology, Criminology, and Media, Culture and Creative Cities. Its faculty, research postgraduate students and post-doctoral fellows, are actively engaged in cutting-edge research and excel in producing excellent scholarly research in the social sciences. The Department is also home to the HKU Anthropology Research Network. Information about the Department can be obtained at https://sociology.hku.hk. HKU Research Hub of Population Studies Launched by the Faculty of Social Sciences at The University of Hong Kong, the HKU Research Hub of Population Studies aims to provide an understanding of local, national, regional, and international demographic patterns, encompassing six research areas: Ageing, Children and Family, Gender and Sexuality, Health and Mortality, Population and Development, and Urbanisation and Migration. The Hub focuses on multi-disciplinary research concerning various population-related issues and public policy, addressing the global needs for theoretical, methodological, and practical advancements in population and health research. The Hub aims to strengthen theoretical, methodological, and policy-relevant research in population and health studies. It serves as a University-wide platform for collaboration among population scientists, promotes the dissemination of cutting-edge interdisciplinary research, and facilitates dialogue between academia, policymakers, and the wider community on evidence-based population policies. The Hub also supports the development of professional training in Population Studies, including demography and data analysis. Further information about the Hub can be obtained at https://www.socsc.hku.hk/rhps/. What We Offer A competitive remuneration package 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 as applicable. The University only accepts online applications for the above post. Applicants should apply online and upload (1) a cover letter, (2) an up-to-date C.V., (3) a research statement and (4) a teaching statement, and state the contact information of three referees on the online application form. At least one of the referees should comment on your research/teaching ability and your contribution to research/teaching in your Department, while the remaining two should have knowledge of your recent academic or employment experience. Review of applications will start as soon as possible and continue until July 31, 2026, or until the post is filled, whichever is earlier.