Technion Israel Institute of Technology

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.

The position is primarily focussed on the delivery of courses within the school’s undergraduate and postgraduate nursing or midwifery programs. You will work with guidance and direction from course coordinators. The role of tutor utilises contemporary professional/discipline-related knowledge in their teaching practice and carries out activities to develop scholarly expertise. Core Responsibilities: Under direction conduct learning activities including lectures, tutorials, assessment and provide timely feedback to students. Use a variety of pedagogical techniques (including face-to-face, online and blended learning) to foster student learning. Undertake high quality teaching as part of the teaching team, including participation in moderation of marking exercises. Incorporate contemporary professional/discipline-based knowledge in teaching activities Act as a student advisor by responding promptly to queries and directing students to appropriate supports/services. Undertake administrative functions connected to courses taught. Actively participate in meetings and committees at the discipline, program and Academic Unit level. Experience Required:  Relevant and recent clinical experience. High level written and oral communication skills including the ability to effectively collaborate with team members, combined with cultural sensitivity. Demonstrated ability to actively engage and educate a student group. Be capable of using the necessary digital technologies required for effective curriculum delivery. High level administrative and organisational skills. Eligibility Requirements: Bachelor of Nursing or Bachelor of Midwifery and relevant postgraduate qualification in a nursing or midwifery specialisation together with current registration, or eligibility for registration, with the Nursing and Midwifery Board of Australia including a current practicing certificate as a Registered Nurse or Midwife. If you have any questions about the process, please contact Dean.SNM@adelaide.edu.au Please note – By registering on the Casual/Sessional Staff Register, it does not guarantee that employment will be offered. If you already hold a casual contract with Adelaide University, please complete the application form to be considered for future opportunities. Applications welcomed from Australian or NZ citizens, Australian permanent residents and those who have the legal right to work in Australia for the term of appointment.

This is an exciting time to join the University of Southampton, a global top-100 university with a reputation for delivering world-class education and research that addresses some of society’s most pressing challenges. We are seeking a Research Fellow in Molecular Dynamics and Computational Chemistry to join the School of Electronics and Computer Science (ECS) at the University of Southampton. The successful candidate will contribute to an interdisciplinary research programme developing computational models to understand molecular interactions relevant to antimicrobial systems, biomolecular interfaces, and catalytic processes. The project will use molecular dynamics simulations to understand molecular mechanisms of metal-based antimicrobial systems and biomolecular interactions, supporting the design of next-generation antimicrobial materials. The role will involve performing molecular dynamics simulations and computational modelling to investigate interactions between biomolecules, materials, and catalytic systems. The postholder will develop and apply advanced simulation techniques, analyse molecular simulation data, and contribute to collaborative research combining computational modelling with experimental studies. You will also contribute to research publications, collaborative research projects, and the development of future research proposals within a multidisciplinary research environment spanning engineering, materials science, and microbiology. About you You will hold a PhD in Computational Chemistry, Chemical Physics, Materials Science, Biophysics, Computational Biology, Biomedical Engineering, or a closely related discipline (or equivalent professional experience). You will have experience in molecular dynamics simulations of biomolecular or materials systems, using simulation platforms such as GROMACS, NAMD, AMBER, LAMMPS, or similar tools. Experience in one or more of the following areas would be advantageous: Biomolecular modelling or enzyme catalysis Metal–biomolecule or catalytic system simulations Quantum mechanical methods (e.g., DFT or QM/MM) Enhanced sampling or free-energy calculations Programming or scripting for computational research (e.g., Python, MATLAB, Bash) You will be motivated to work in a multidisciplinary research environment, collaborating with experimental scientists and computational researchers to develop innovative computational approaches that support interdisciplinary research. What we can offer you We offer some fantastic benefits including generous annual leave (plus an additional 6 University closure days and bank holidays), a company pension scheme, discounted private healthcare and dental, company sick pay, flexible working options, and excellent family leave arrangements. You will benefit from access to the University’s excellent research infrastructure, training and development opportunities, and a vibrant interdisciplinary research environment. Southampton is a dynamic coastal city with excellent transport connections and offers a fantastic place to live, work and collaborate. Equality, diversity and inclusion We are proactive in fostering a culture of inclusion, respect and equality of opportunity. We select candidates based on merit and ability and aspire to thrive in the diversity of our workforce.