Al Ghurair University

Job Description As part of our laboratory's research initiatives, we are conducting advanced research on the computational modeling and optimization of heterogeneous catalysts for various catalytic processes. This project focuses on utilizing computational techniques to understand and enhance the performance of catalysts in reactions such as hydrogenation, oxidation, and biomass conversion. We are seeking a highly motivated candidate to contribute to the development of new catalytic systems through computational simulations and theoretical studies. Main Responsibilities: Perform computational calculations to model and optimize heterogeneous catalysts. Conduct simulations to evaluate catalytic performance and reaction mechanisms. Analyze and interpret computational data to understand the interactions between catalysts and reactants. Write scientific reports and research articles and participate in conferences. Candidate Profile PhD degree in Chemical Engineering, Materials Science, or a related field. Strong knowledge of heterogeneous catalysis and computational chemistry. Experience with computational modeling  (i,e, DFT, and/or molecular dynamics). Familiarity with software such as Material Studio, VASP, Quantum Espresso… Excellent communication skills (oral and written) in English. Good publication track record in peer-reviewed journals. Ability to work independently and as part of a multidisciplinary and multicultural team. Experience in co-supervision and coordination of graduate students is desirable. Candidature Submission: Applicants should submit: Cover letter outlining research experience, and achievements, and stating research interests. Curriculum Vitae. List of publications. Name and contact information of at least two referees. Recommendation letter.

Institution/Department Mohammed VI Polytechnic University Chemical & biochemical sciences.green process engineering Research Unit on Microbiome and Host-Pathogen Interactions Project Overview: We are looking for a highly motivated Postdoctoral Research Fellow to join our interdisciplinary team focused on antimicrobial resistance (AMR). The selected candidate will have a vital role in an innovative project that aims to map the resistome and clarify the mechanisms of multidrug resistance across diverse microbiomes—comprising clinical, environmental, and host-associated microbial communities. This project seeks to comprehend how antimicrobial resistance genes (ARGs) disseminate within microbial populations via horizontal gene transfer (HGT) and mobile genetic elements (MGEs) and how these processes affect human health, particularly regarding colorectal cancer (CRC). Key Responsibilities: Perform shotgun metagenomics and whole-genome sequencing (WGS) on microbial samples from various environments (clinical, environmental, tumor-associated microbiomes). Develop and implement bioinformatics pipelines for resistome, mobilome, and virulome profiling using tools such as MEGARes, CARD, VFDB, and PlasmidFinder. Investigate horizontal gene transfer (HGT) dynamics and plasmid-mediated dissemination of ARGs across microbial communities. Conduct phylogenetic and comparative genomic analyses to uncover the evolution of multidrug resistance in pathogenic bacteria. Analyze co-occurrence networks between resistance genes, virulence factors, and mobile elements in microbiome datasets. Collaborate with clinical partners and microbiome researchers to integrate multi-omics data for comprehensive resistome analysis. Publish high-quality research articles and present findings at international conferences. Contribute to grant writing and development of new research proposals. Required Qualifications: PhD in Microbial Genomics, Bioinformatics, Molecular Microbiology, Infectious Disease Biology, or a related field. Proven experience with high-throughput sequencing technologies (Illumina, Nanopore) and metagenomic analyses. Strong background in bioinformatics tools for microbiome analysis (QIIME2, Kraken2, MetaPhlAn) and AMR gene identification (MEGARes, CARD, ResFinder). Proficiency in Python, R, or Perl, with experience in Linux/Unix environments. Solid understanding of antimicrobial resistance mechanisms, horizontal gene transfer, and mobile genetic elements. Evidence of scientific publications in peer-reviewed journals. Excellent communication and teamwork skills. Preferred Qualifications: Experience in clinical microbiome research, oncology microbiomes, or environmental resistome surveillance. Familiarity with spatial metagenomics, single-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning approaches for resistome prediction or biomarker discovery is a plus. Why Join Us? Access to cutting-edge technologies (mass spectrometry, next-gen sequencing, high-performance computing). Work on high-impact research addressing one of the urgent challenges in global health—antimicrobial resistance. Collaborate with a multidisciplinary team of microbiologists, bioinformaticians, clinicians, and data scientists. Opportunity to lead high-profile publications and contribute to international consortia. Career development support, including grant writing, conference funding, and training opportunities. Application Process: Applicants should submit the following in a single PDF file: A Cover Letter explaining their interest and fit for the position A detailed Curriculum Vitae (CV) Names and contact details of 2–3 references Up to three key publications (optional)

Lingnan University is one of the eight publicly funded institutions in the Hong Kong Special Administrative Region (HKSAR) of the People’s Republic of China (PRC) 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: Associate Professor of Teaching / Assistant Professor of Teaching Department of Management (Post Ref.: 26/32) The Department of Management (http://www.LN.edu.hk/mgt/) is one of the constituent departments that contribute to the undergraduate programme of Bachelor of Business Administration (Hons) degree. The Department offers a variety of courses in Management and aims to equip students with the knowledge, skills, and qualifications to meet the needs of a thriving business centre like Hong Kong. The primary responsibilities of the appointee include teaching and supporting the University’s educational mission. The appointee is expected to teach a variety of core and elective courses, develop new programmes, courses, teaching methods and procedures to enhance students’ learning. Additionally, appointee is encouraged to apply for teaching grants, organize knowledge transfer activities, and take responsibility for facilitating such initiatives. Candidates with advanced qualifications and more extensive experience may be considered for higher-level appointments. General Requirements For appointment as Associate Professor of Teaching / Assistant Professor of Teaching, candidates should have a doctoral degree in the relevant discipline, with a distinguished teaching record with professional recognition through leadership in the field of education, and should commit to teaching excellence, curriculum development, programme coordination, promotion and management, student advising and mentoring. Appointment The conditions of appointment will be competitive. The rank and remuneration will be commensurate with qualifications and experience. Fringe benefits include annual leave, medical and dental benefits, mandatory provident fund, gratuity, and incoming passage and baggage allowance for the eligible appointee. Appointment will normally be made on a fixed-term contract of up to three years. Application Procedure (online application only) Please click Apply Now to submit your application. Applicants should provide a CV and information about their work experience, qualifications, research interests and achievements. A statement of their publications and of any works in progress currently under review are required. Applicants should 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.