Creighton University

The School of Chemistry and Chemical Engineering at the University of Surrey invites applications for a full-time Postdoctoral Research Fellow position, focussing on mechanistic modelling of pharmaceutical processes. This role offers a unique opportunity to join a dynamic research team focused on advancing the understanding of pharmaceutical formulation and manufacturing processes. The role The post holder will develop and implement mechanistic models to analyse and predict the behaviour of pharmaceutical processes. Your work will address key challenges within these processes, constructing robust models and simulations that deepen the understanding of the underlying physics involved. The ultimate goal is to create predictive, physics-based models that optimise and control pharmaceutical manufacturing processes effectively. Your main responsibility is to develop and enhance discrete element models (DEM), integrating physics-based mechanistic models to simulate complex fluid and particulate systems. About you This role requires independent initiative, teamwork, and a proactive approach to problem-solving and innovation in pharmaceutical process modelling. The ideal candidate will possess a strong numerical background with proficient programming skills and a proven research record through publications and code development. Experience in developing discrete element models (DEM) or hybrid models, such as DEM-CFD or DEM-SPH, is essential. For this position, a doctoral degree in a relevant discipline is required, although candidates nearing completion may be considered. Exceptional candidates with extensive experience may also be considered. The project involves collaboration with UK and international universities and industry partners, so strong teamwork and communication skills are essential. This is a unique opportunity for motivated candidates to contribute significantly to cutting-edge research in pharmaceutical process modelling. How to apply Please apply on the University website with your CV and cover letter also answering the criteria questions. Further details Job Description

Ref.: 533703 Work type: Full-time Department: Department of Data and Systems Engineering (14400) Categories: Senior Research Staff & Post-doctoral Fellow, Research Staff We are seeking highly motivated researchers to join our project on “Planning and Scheduling of Automated Material Handling Systems in Semiconductor Manufacturing Environments.” This project is carried out in collaboration with leading semiconductor companies and targets real-world, industrially relevant challenges. Our goal is to advance cutting-edge research while ensuring strong practical applicability. The research will concentrate on three interrelated areas:  a) Semiconductor Equipment Scheduling: In semiconductor fabs, a vast number of wafers are processed across hundreds or even thousands of manufacturing tools following highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences across semiconductor manufacturing tools, with the objectives of reducing cycle times and lowering work-in-progress (WIP) inventory, thereby increasing throughput and overall manufacturing efficiency. b) Automated Material Handling System (AMHS) Scheduling: In modern semiconductor fabs, AMHS, typically realized through Overhead Hoist Transport (OHT), is responsible for transferring wafers between manufacturing tools. Given the massive production scale, the AMHS must handle tens of thousands of transports requests every day, ensuring timely and reliable delivery of wafers to the correct tools. Our research seeks to develop efficient and adaptive scheduling algorithms for AMHS systems to significantly reduce transport delays, improve material flow, and enhance coordination between logistics and manufacturing processes. c) Digital Twin System: We aim to construct a digital twin framework that integrates real-time data and simulation models to mirror the physical manufacturing and logistics systems. This enables performance monitoring, predictive analysis, and the evaluation of scheduling strategies in a virtual environment, thereby supporting more robust and adaptive decision-making in semiconductor manufacturing. Responsibilities:  a) To address the above challenges, applicants are expected to formulate mathematical models of the problems and develop efficient solution methods, particularly by leveraging techniques from machine learning and operations research. b) The applicants are expected to deliver research outcomes to our industry partners, to support practical applications in semiconductor manufacturing. c) The applicants are expected to write and submit high-quality academic papers. Qualifications a) Education: Ph.D. in Automation, Industrial Engineering, Systems Engineering, Computer Science, or a closely related field. b) Technical Skills: Strong programming proficiency is required. c) Research Experience: Relevant research experience in related problem domains, or research experience in scheduling, routing, and multi-agent pathfinding (MAPF) algorithms - Experience across multiple areas is a strong plus; Experience developing ML-based optimization approaches is a strong plus; A strong publication track record is highly desirable. d) Industry collaboration experience: Prior experience in collaborative R&D with industry partners is a strong plus. Application: Send your CV, a cover letter, and the contact information of three referees to Dr. Anbang Liu (anbang@hku.hk) and cc to Prof. Lin (shaoclin@hku.hk). The complete reference letters should be submitted as soon as possible after the application.

Manage sites and activities that demonstrate drought resilience and improve the natural environment. Collaborative team environment delivering world-class research and end-user adoption. Full-time appointment on a fixed term basis for 2 years. Base salary range: Level B, $118,150 – $139,812 p.a. (pro-rata) plus 17% superannuation. About the area The Centre for Water and Spatial Science (CWSS) is a multidisciplinary team of researchers and project staff, working with industry collaborators and research funding organisations to address challenges related to water resources, a changing climate and using advanced spatial science methods. CWSS sits within the UWA School for Agriculture and Environment at The University of Western Australia (UWA), but also includes leading geospatial science, water science and engineering researchers from schools including Earth and Oceans, and Engineering. CWSS provides research leadership in water and spatial science in Western Australia and is a preferred research partner for national and international projects. About the opportunity Lead project field data science related to quantifying water security and biodiversity. Deliver outreach and adoption that translate research onto action. Manage project partnerships across university, NRM NGOs, grower groups and farm enterprises. About you A PhD in geography, hydrology, spatial sciences, environmental engineering, environmental science, catchment science or a related discipline; or equivalent experience. An established or emerging track record of excellence in research, evidenced by high-quality and high-impact, published scholarly research and reports. Experience and skills in water and/or spatial science and engineering, including experimental design, instrumentation, data collection, data archiving, and project management. Ability to undertake complex analyses and data modelling using programming languages such as Python, R and/or hydrological modelling packages, with adherence to FAIR data principles (Findable, Accessible, Interoperable and Reusable). Experience in coordinating and undertaking field research (including in rural and regional locations), with adherence to safe working practices and meeting work health and safety obligations. Note: Employment checks will include information on gender-based violence, sexual harassment, and related misconduct to meet legal obligations. A “C” class driver’s licence will be required by the successful applicant. Position description: PD - Research Fellow (522889).pdf To learn more about this opportunity, please contact Professor Nik Callow at Nik.callow@uwa.edu.au  How to apply Please apply online via the Apply Now button and address the selection criteria in your submission in a separate document. For information to assist you with compiling statements to answer the selection criteria, please visit Addressing the selection criteria. You may submit a statement describing any personal circumstances relevant to your application. This can include academic/professional interruptions or achievements relative to opportunity. Closing date: 11:55 PM AWST on Sunday, 29 March 2026. This position is only open to applicants with relevant rights to work in Australia. Benefits Flexible working options. Generous paid leave including parental leave. Up to 17% employer paid superannuation. Salary packaging available. Incremental progression based on 12 months continuous service. Discounted UWA course fees. Discounted health insurance. Employee Assistance Program. About the University The University of Western Australia (UWA) is ranked among the top 100 universities in the world and a member of the prestigious Australian Group of Eight research intensive universities. With a strong research track record, vibrant campus and working environments, supported by the freedom to innovate and inspire, there is no better time to join Western Australia’s top university. Learn more about us. Our commitment to inclusion and diversity UWA is committed to a diverse workforce and an equitable and inclusive workplace. We are committed to fostering a safe environment for all, including Aboriginal and Torres Strait Islander people, women, those from culturally and linguistically diverse backgrounds, the LGBTIQA+ community, and people living with disability. If you require any reasonable adjustments, we encourage you to advise us at the time of application. Alternatively, you can contact us for assistance during the recruitment process. If you have queries relating to your application, please contact the individual named in the advertisement. Alternatively, please contact the Talent team at people@uwa.edu.au with details of your query. To enable a quick response, please include the 6-digit job reference number.