Doctoral Researcher in quantum computing and algorithms for Life Science applications

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Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with 14 000 students and a staff of 5000, of which more than 400 are professors. Our main campus is located in Espoo, Finland. Diversity is part of who we are, and we actively work to ensure our community's diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. The School of Electrical Engineering is one of the six schools of Aalto University. Our portfolio covers fields from natural sciences to engineering and information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care of the elderly to space robotics. We are now looking for a d octoral researcher in quantum computing and algorithms for Life Science applications. Are you as excited about quantum technology and its future applications as we are? We are seeking a doctoral researcher to join the Micro and Quantum Systems (MQS) research group in the Department of Electronics and Nanoengineering at Aalto University. MQS currently comprises more than 18 members and is expanding. We are advancing foundational topics in quantum computing and their practical applications. In this position, you will work at the intersection of quantum computing, computational biology, genomics, and materials science. You will have the opportunity to delve deeply into quantum computing and contribute to high-quality research with real-world impact. Join us in shaping the future! Your role and goals Your primary task as a doctoral researcher is to conduct research in quantum algorithms and quantum information, leading to the completion of your PhD. You are expected to take an active role in advancing the MQS group's research projects. Our recent work has focused on the theory and applications of quantum walk algorithms, variational quantum algorithms and their optimization, adiabatic quantum computation, and quantum machine learning. Theoretical and applied research into the capabilities of quantum computing and quantum advantage is a prospective topic across four application domains: bioinformatics, breeding, biomaterial synthesis, and cellulose‑processing enzyme design. You will develop hybrid quantum‑classical algorithms to tackle domain‑specific, computationally demanding problems. Methods will be designed for near‑term (NISQ‑era) deployment, with models evaluated for expressivity, training stability, scalability, and resource requirements on representative problem sizes, and systematically benchmarked against fully classical baselines. In parallel, medium‑ to long‑term quantum algorithms will be explored to assess quantum readiness and to establish innovative methodologies relevant to each application field. The exact research topics can be tailored to your interests within the scope of our current projects. Your goal is to produce world‑class research results, in collaboration with other group members in the lively environment of the MQS group, and to publish them in high‑impact journals. In addition to research, you will be expected to take doctoral coursework and participate in the group's teaching activities. Your network and team Currently, our research group consists of 1 professor, 1 lecturer, 1 staff scientist, 2 postdocs and 5 PhD students, and several undergraduate research collaborators. The group is led by Professor Ilkka Tittonen. Your experience and ambitions Applicants are expected to hold a Master's degree and excellent study records in theoretical physics, mathematics, computer science, or other relevant field. have a keen interest in quantum computing have a working proficiency in English. (Finnish language is not required.) The research topics can be adjusted according to the background of the applicant. Familiarity with the areas outlined in this call is a clear advantage. Teaching experience will also be a valuable asset.

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