The Quantum AI lab at ETH Zürich, led by Prof. Juan Carrasquilla, is recruiting PhD students to work at the intersection of computational quantum many-body physics, machine learning, quantum computing, and non-Hermitian systems. This research group is engaged in advancing the second quantum revolution, leveraging machine learning to explore complex quantum systems and using quantum effects to push the boundaries of artificial intelligence. The lab’s long-term goal is to extend machine learning methodologies to solve critical problems in quantum many-body physics, with broad implications for condensed matter theory, quantum materials, chemistry, and quantum technology. As a PhD student, you will address fundamental questions such as simulating Hermitian and non-Hermitian strongly correlated quantum systems and harnessing both classical and quantum computing resources. You will also explore how quantum physics can inspire the development of cutting-edge machine learning algorithms. The position involves deep theoretical and computational work, focusing on algorithm development and large-scale numerical simulations. Techniques such as quantum Monte Carlo, tensor networks, and quantum machine learning will be central to your research, enabling you to tackle challenges in equilibrium and out-of-equilibrium quantum systems, quantum computing, and machine learning. The lab offers a collaborative and supportive environment, access to state-of-the-art computational facilities, and opportunities for internal and international collaboration. You will have the freedom to develop your research ideas, mentor students and interns, and define a work schedule that fits your preferences. ETH Zürich is renowned for its excellence in science and technology, diversity, and commitment to sustainability. The university fosters an inclusive culture and provides a climate-neutral future-oriented environment. To apply, submit your CV, academic transcripts, a brief statement of research interests, and contact information for at least two academic referees via the ETH online application portal. Applications are reviewed on a rolling basis, and positions remain open until filled. For further information about the position or the group, contact Prof. Juan Carrasquilla at [email protected] (no applications via email).

The Quantum AI lab at ETH Zurich, led by Professor Juan Carrasquilla, is inviting applications for PhD and postdoctoral positions focused on computational quantum many-body physics, machine learning, quantum computing, and non-Hermitian systems. The lab's research aims to advance the intersection of quantum physics and machine learning, tackling fundamental questions in condensed matter theory, quantum materials, and quantum chemistry. Successful candidates will develop and apply algorithms and large-scale numerical simulations, including quantum Monte Carlo, tensor networks, and quantum machine learning techniques, to address challenges in equilibrium and out-of-equilibrium quantum systems. The group offers a collaborative and inclusive environment, access to advanced computational resources, and opportunities for both independent and team-based research. Applicants should have a strong background in physics, mathematics, or computer science, with excellent coding and leadership skills. The positions are fully funded, with flexible start dates in 2025 and 2026, and applications are accepted until the positions are filled. For more information, contact Professor Juan Carrasquilla at ETH Zurich.

The Quantum AI Lab at ETH Zürich, led by Prof. Juan Carrasquilla, is inviting applications for PhD positions focused on computational quantum many-body physics, machine learning, and non-Hermitian systems. This opportunity places students at the intersection of quantum physics and artificial intelligence, contributing to the ongoing second quantum revolution. The lab's research aims to advance the use of machine learning in solving critical problems in quantum many-body physics, with broad implications for condensed matter theory, quantum materials, chemistry, and quantum technology. As a PhD student, you will tackle fundamental questions such as simulating Hermitian and non-Hermitian strongly correlated quantum systems and leveraging both classical and quantum computing resources. The position involves developing algorithms and conducting large-scale numerical simulations, with expertise spanning quantum Monte Carlo, tensor networks, quantum computing, and quantum machine learning. Your work will address challenges in equilibrium and out-of-equilibrium properties of quantum systems, contributing to advancements in both theoretical understanding and computational capabilities. ETH Zürich offers a collaborative and inclusive environment, valuing diversity and sustainability. Students have the freedom to develop their research ideas, collaborate with ETH faculty and international partners, mentor students and interns, and access state-of-the-art computational facilities. The group fosters a supportive atmosphere and flexible work schedules tailored to individual preferences. Applicants should hold a Master's degree in physics, mathematics, applied mathematics, or computer science, and demonstrate strong interest and skills in theoretical or computational quantum physics, quantum computing, or machine learning. Coding proficiency, leadership, and the ability to work both independently and collaboratively in a diverse team are essential. To apply, submit your application online via the ETH portal, including your CV, academic transcripts, a brief statement of research interests, and contact information for at least two academic referees. Applications are reviewed on a rolling basis and positions remain open until filled. For further information about the position or the group, contact Prof. Juan Carrasquilla at [email protected] (note: no applications via email). ETH Zürich is a world-leading university in science and technology, renowned for excellence in education and research. Located in Zurich, Switzerland, it provides a vibrant international community and a stimulating environment for independent thinking and academic growth.

The Quantum AI lab at ETH Zürich, led by Prof. Juan Carrasquilla, is seeking postdoctoral researchers to work at the intersection of computational quantum many-body physics, automated scientific discovery, and machine learning. This position offers the opportunity to contribute to the second quantum revolution, where machine learning is increasingly used to explore complex quantum systems, with significant implications for materials science, quantum chemistry, and quantum technology. The lab's long-term goal is to extend the applicability of machine learning to solve critical problems in quantum many-body physics, impacting condensed matter theory, quantum materials, and beyond. As a postdoctoral researcher, you will address fundamental questions such as simulating strongly correlated quantum systems using both classical and quantum computing resources and automating the scientific process to enable new breakthroughs. The role involves engaging with a diverse array of concepts at the intersection of artificial intelligence, condensed matter physics, and quantum computing. The position is full-time, with flexible starting dates in 2025 and 2026. Applicants should have a PhD in quantum physics, computer science, or applied mathematics, and a strong interest in developing theoretical or computational methods for quantum many-body systems, quantum computing, or machine learning. Leadership skills, the ability to collaborate with a diverse group, and the capacity to work independently and in teams are essential. Experience with large language models and automation is desirable. The lab offers a supportive environment, opportunities for internal and international collaboration, mentoring of students and interns, access to state-of-the-art computational facilities, and travel to conferences. ETH Zürich is a world-leading university in science and technology, known for its commitment to diversity, sustainability, and excellence in research and education. Applications should be submitted online, including a CV, research statement, and contact information for at least two referees. The review of applications begins immediately and continues until the positions are filled. For further information, contact Prof. Juan Carrasquilla at [email protected] (no applications via email).