Georgetown University - McDonough School of Business

Applications are invited for a Postdoctoral Research Associate in chemical biology with a strong focus on biocatalysis. The associate will join a multi-disciplinary research team within the Schnepel group that focuses on the development of novel biocatalysts for the synthesis of fine chemicals, pharmaceuticals and bioconjugation chemistry. The research project led by Dr Christian Schnepel will involve the discovery, development and study of biocatalysts for the synthesis of peptide-based therapeutics. The successful applicant will be expected to work closely with the industry partner Johnson & Johnson in Belgium to develop cutting-edge bio-synthetic methodologies for drug discovery and large-scale manufacturing. This post is fixed term for 12 months. The MRC funding is available for this fixed period only. The post-holder is employed to work on research/a research project which will be led by another colleague. Whilst this means that the post-holder will not be carrying out independent research in his/her own right, the expectation is that they will contribute to the advancement of the project, through the development of their own research ideas/adaptation and development of research protocols. Successful applicants will, ideally, be in post by 1st April 2026. Department contact for academic-related enquiries Dr Christian Schnepel.

About us  King’s College London invites applications for a Research Assistant (RA) in GeoAI, Infectious Diseases, and Health Equity to join the GeoAI for Health Equity Lab (GAHEL, pronounced “gail”) led by Dr. Sabrina Li. The RA will contribute to Dr. Li’s UKRI-funded Future Leaders Fellowship project which focusses on integrating equity considerations into infectious disease mapping and surveillance, starting with the UK. The RA will be based in the Department of Geography, but will have access to training and support from King’s Health Partners Digital Health Hub, King’s Institute for Artificial Intelligence, and the Digital Futures Institute. The RA will also have access to research and career development from King’s Centre for Research Staff Development. The postholder will work closely with Dr. Li and in collaboration with national and international interdisciplinary partners based at the UK Health Security Agency (UKHSA), University of Cambridge, Imperial College London, and John Hopkins University (USA). About the role The RA will contribute to the theoretical and methodological developments of scalable GeoAI systems that improve understanding of infectious disease risks across populations and space, particularly for vulnerable and disadvantaged populations. The RA will lead literature review searches to identify the historical, structural, and contextual drivers of disease risk and inequity, and map pathways and interactions among determinants to inform disease mapping and modelling.  The RA will lead the development of a database of high-resolution equity indicators for disease surveillance, and will contribute to the development of novel approaches for managing confidential spatial health data, including differential privacy and other secure geospatial data protocols. This research will advance our understanding of how major infectious diseases of concern in the UK emerge, spread, and unequally affect different individuals and population groups. Outcomes of this research will help advance the development of more equitable, spatial data-driven approaches to public health surveillance and pandemic preparedness, with direct links to public health policy. The findings will inform the development of a real-time spatial AI system to improve early detection and risk prediction, to protect vulnerable populations in the UK and in the future globally. This is a full-time post (35 hours per week), and you will be offered a 2-year fixed-term contract. The post is offered on a hybrid working basis, typically involving three days per week on campus and two days remote.  Research staff at King’s are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers, applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria  PhD in spatial epidemiology, quantitative geography/remote sensing, ecology, statistics, engineering, data science, quantitative social sciences, or a related discipline.  Experience in developing models and mapping with real world data, with strong programming proficiency in R or Python and version control systems like Git. Familiarity with spatial and statistical libraries (e.g. INLA, PyMC, scikit-learn, GeoPandas). Proven ability to work independently. Track record in publishing peer-reviewed papers. Demonstrated ability to collaborate effectively within teams, with a strong commitment to fostering a fair and inclusive work environment. Excellent written and oral communication skills, including to diverse audiences.  Desirable criteria Experience managing stakeholder relationships and working in a practitioner/policy context. Experience working on interdisciplinary research projects. Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.  Further information We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community. We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's. As part of this commitment to equality, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities. We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible. To find out how our managers will review your application, please take a look at our ‘How we Recruit’ pages. Interviews are due to be held between Monday 19th - Friday 23rd January 2026. Grade and Salary: £39,735 per annum including London Weighting Allowance Job ID: 134808 Close Date: 11-Jan-2026 Contact Person: Sabrina Li Contact Details: sabrina.li@kcl.ac.uk

Location Abu Dhabi, United Arab Emirates Open Date Nov 20, 2025 Deadline Aug 31, 2026 at 11:59 PM Eastern Time Description MBZUAI is a research-focused university in Abu Dhabi, and the first university dedicated entirely to the advancement of science through AI. The university empowers the next generation of AI leaders, driving innovation and impactful applications of AI through world-class education and interdisciplinary research. In 2025, MBZUAI launched its first ever undergraduate program, a Bachelor of Science in AI, with two distinct streams: Business and Engineering, and are looking for passionate and highly motivated Teaching Faculty. The Undergraduate Division is seeking teaching faculty in Natural Language Processing (NLP) & AI to deliver and manage the course, "The Language of AI".  This course introduces students to Natural Language Processing (NLP) and Information Retrieval (IR), providing a foundational understanding of how computers process, analyze, and retrieve human language data. Students will explore key concepts such as tokenization, document indexing/ranking/classification, document indexing and ranking, and word and document embedding methods, while gaining hands-on experience with basic algorithms and tools used in NLP and IR. The course also explores practical applications, including search engines, chatbots, and text classification systems. It will also present and refresh the relevant deep learning architectures on which recent LLM architectures capitalise on (including transformers). This course introduces the fundamental LLMs data and architecture pipeline.  Responsibilities include: Delivering high-quality instruction in Natural Language Processing and related topics Developing and updating course materials, assessments, and lab exercises to reflect current advances in NLP and AI Fostering an engaging and inclusive learning environment that promotes active student participation Supervising student projects and providing academic mentoring Contributing to curriculum enhancement and continuous improvement in teaching quality Why Join MBZUAI? Top-Tier Compensation: Competitive salaries aligned with leading global academic institutions Exceptional Benefits: Comprehensive health & life insurance Relocation support for international faculty Live in Abu Dhabi: World’s safest city, year-round sunshine, rich culture, and modern amenities Industry & Government Collaborations: Work with top AI researchers, leading tech firms, and policymakers Qualifications This position requires a PhD in Computer Science, Artificial Intelligence, Data Science or Engineering, Computational Linguistics, or a closely related discipline. Demonstrated expertise in Natural Language Processing, Information Retrieval, and related areas. Experience with modern NLP frameworks (e.g., NLTK, spaCy, Hugging Face Transformers, TensorFlow, PyTorch). Teaching Experience: Proven teaching or training experience at the undergraduate or graduate level (or equivalent professional training experience) Application Instructions To apply for this position, please submit the following: Cover letter Curriculum Vitae Teaching statement Reference letters or Name and contact details for three referees *MBZUAI's mission includes fostering a diverse academic community. MBZUAI is an equal opportunity employer. The university actively recruits faculty from around the world, aiming to create an international and inclusive environment that reflects a wide range of cultures and perspectives. *Be part of AI’s future—apply today to MBZUAI! *#MBZUAI #careeropportunities #AI