This opportunity is for an early career researcher to join a team advancing the study of quantum algorithms through the development and scaling of high-performance numerical methods. The research focuses on quantum computing, particularly the simulation and optimization of quantum algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) applied to complex systems like the Sherrington-Kirkpatrick spin glass model. Projects include scaling up matrix product state (MPS) simulations on supercomputers and performing exact tensor network contractions to demonstrate beyond-classical applications of near-term quantum computers, such as certified randomness expansion and amplification. The position is based at Universiti Malaysia Sabah and is announced by Muhammad Ismail, a Physics Professional and Founder of the British Online Academy, with a strong background in research, technical writing, and quantum computing education. The role is suitable for recent graduates (Senior Associate) or those with more than two years of post-PhD experience (Vice President), with a focus on computational physics, quantum information, and high-performance computing. Applicants should have expertise in quantum computing, numerical methods, and computational physics, with experience in high-performance computing environments and familiarity with tensor networks and quantum algorithms. The research is closely linked to recent advances published in leading journals and preprints, including work on the efficiency of QAOA for the SK model and certified randomness using quantum processors. While specific funding details are not provided, the position is a paid research scientist role. Interested candidates are encouraged to apply via the provided online job portals, ensuring their qualifications align with the requirements for each role. The research environment offers opportunities to contribute to cutting-edge projects at the intersection of physics, computer science, and mathematics, with access to world-class computational resources and collaborations. For more information, review the linked publications and job descriptions, and contact the announcer via LinkedIn if needed.

Postdoctoral positions are available in the research group led by Muhammad Ismail at Universiti Malaysia Sabah, Malaysia. The group is seeking 1–2 postdocs to contribute to cutting-edge research in deep reinforcement learning, traffic modeling and control, and neural combinatorial optimization. The overarching mission is to leverage artificial intelligence and machine learning to address challenging optimization problems and enable evidence-driven decisions in real-world socio-technical systems. Research areas include deep reinforcement learning, traffic modeling and control, neural combinatorial optimization, and the application of AI/ML techniques to complex optimization scenarios. The group is particularly interested in candidates with expertise in machine learning, optimization, and the development of innovative solutions for socio-technical systems. Applicants should hold a PhD in computer science, mathematics, engineering, or a related discipline. Preferred qualifications include a strong background in deep reinforcement learning, traffic modeling, neural combinatorial optimization, or artificial intelligence. Experience with machine learning, optimization, and evidence-driven decision-making is highly valued. Excellent research and communication skills are essential. Applications are reviewed on a rolling basis, with positions available immediately. Interested candidates should visit the provided application link for further details and instructions on how to apply. The group encourages applications from individuals with diverse backgrounds and a passion for advancing research in AI and optimization. For more information about the group and research topics, please refer to the supervisor's LinkedIn profile and the application link. Funding details are not specified in the announcement; candidates are encouraged to inquire directly regarding salary, benefits, and funding structure.

A postdoctoral researcher is sought to collaborate on an application for the ANID – FONDECYT Postdoctoral Fellowship 2027, working with Muhammad Ismail's group at Universiti Malaysia Sabah. The group specializes in advanced functional materials for environmental and energy applications, with particular emphasis on photocatalysis, semiconductor heterojunctions, and contaminant removal. The successful candidate will help develop a research proposal that aligns both with the group’s expertise and their own research background. Applicants must hold a PhD in Chemistry, Materials Science, Chemical Engineering, or a closely related field, with the degree awarded in 2023 or later, in accordance with ANID FONDECYT eligibility criteria. A strong publication record is required, as is a background in photocatalysis, nanomaterials, or environmental remediation. Proficiency in both spoken and written Spanish is essential for this opportunity. To apply, candidates should email a CV (including publications from the last 5 years) and a 1-page statement outlining their research idea and its fit with the group to [email protected]. Only complete applications sent by email will be considered, and shortlisted candidates will be contacted to further develop the proposal for submission to ANID FONDECYT 2027. Please refrain from making inquiries via LinkedIn messages. This opportunity is ideal for researchers interested in advanced materials, environmental science, and energy applications, and offers the chance to work in a dynamic, interdisciplinary group at Universiti Malaysia Sabah. Funding is dependent on the success of the ANID FONDECYT application and will follow the fellowship’s standard terms, typically including a stipend and research support. For more information about the group or the position, refer to the provided LinkedIn profile.