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  • Doctoral Researcher (Ph.D. position) in Generative Machine Learning for Quantum Matter
    T304 Dept. Applied Physics
    Aalto University

    [i]Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors and close to 4 500 other faculty and staff working on our dynamic campus in Espoo, Greater Helsinki, 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.[/i]

    The Department of Applied Physics is now looking for a
    [i] [/i]
    [b]Doctoral Reseracher in Generative Machine Learning for Quantum Matter [/b]

    We invite applications for a Ph.D. position in the field of generative machine learning for quantum many-body matter. The prospective Ph.D. researcher will work on designing quantum phenomena with a combination of many-body and machine-learning techniques. In particular, the project will exploit quantum many-body methods in combination with generative adversarial machine learning methods, including transformer and diffusion models. The prospective Ph.D. researcher will ultimately develop generative machine learning methodologies to design novel correlated states combining theoretical and experimental data.
    [b] [/b]
    [b]Your role and goals[/b]

    Correlated quantum materials provide a powerful playground to explore unconventional physics beyond those occurring in conventional materials. In many instances, a variety of quantum states compete in the same quantum material. This gives rise to a complex interplay between subtle effects appearing simultaneously, making the identification of many-body states a greatly challenging task. In particular, extracting the mathematical description of a quantum many-body system, namely its Hamiltonian, from observable quantities remains a greatly challenging and open problem. You will tackle this challenge by combining techniques from generative machine learning with quantum manybody methods to develop methodologies capable of extracting Hamiltonian descriptions from complex observables. The project will initially focus on developing these generative learning methodologies with synthetic computational data in the first stage and extending them with a combination of synthetic and experimental data in the final stage.

    As a Ph.D. researcher, you will combine two techniques from generative adversarial learning, transformer networks and diffusive models, with modern methods for quantum many-body matter, including tensor-network and neural-network quantum states. The project will focus on applying these generative learning methodologies to emergent macroscopically entangled states of matter, giving rise to fractionalized excitations, including quantum magnets and unconventional superconductors. The project will focus on extracting quantum description from experimentally observable quantities, with the aim of deploying generative machine learning for quantum matter design. The project will provide you with a strong background in generative machine learning and emergent quantum matter.
    [i] [/i]
    [b]Your experience and ambitions[/b]

    The Ph.D. project will be carried out in the group “Correlated Quantum Materials” led by Prof. Jose Lado at Aalto University. We look for highly motivated individuals with i) a solid background in theoretical quantum physics and interest in machine learning or ii) a solid background in machine learning and an interest in theoretical quantum physics.

    We require the candidates to have excellent skills in English. Finnish language is not required. To be eligible, candidates must hold a master’s degree in a suitable field.

    [b]What we offer [/b]

    Following the standard practice in the Department of Applied Physics, the contract will be made initially for two years, then extended to another two years after a successful mid-term progress review. The total duration of Ph.D. studies is four years. The annual workload of research and teaching staff at Aalto University is currently 1612 hours. Aalto University follows the salary system of Finnish universities. The starting salary of a PhD student is approximately 2600 €/month (gross), and it increases as you progress in your research and studies. The contract includes Aalto University occupational healthcare.

    Our vast array of professional development opportunities means you will grow and learn, having the chance to participate actively in staff trainings and development projects based on your interests and needs. There is great freedom in your role, and we have a flexible modern working culture. We value work-life balance and well-being in all aspects of life.

    We work in a hybrid way, and the primary workplace is Otaniemi, Espoo. The Otaniemi campus is a thriving and connected community of 100 nationalities, 13,000 students and 4,500 employees. Life at the transformed campus is vibrant and filled with amazing architecture, calming nature, and a variety of cafes, restaurants, services and good connections along the recently opened metro line.

    [b]Join us![/b]

    To apply for the position, please submit your application including the attachments mentioned below as one single PDF document in English through our online recruitment system by using the link on Aalto University’s web page ("Apply Now”).

    (1)   Letter of motivation
    (2)   CV including list of publications
    (3)   Degree certificates and academic transcripts
    (4)   Contact details of at least two referees (or letters of recommendation, if already available)

    [b]The deadline for applications is May 20, 2023.[/b] We will go through applications, and we may invite suitable candidates to interview already during the application period. The position will be filled as soon as a suitable candidate is identified. For additional information, kindly contact [b]Prof. Jose Lado[/b] ( Aalto University reserves the right for justified reasons to leave the position open, to extend the application period, reopen the application process, and to consider candidates who have not submitted applications during the application period.

    Please note: Aalto University’s employees should apply for the position via our internal system Workday -> find jobs (not external webpage on open positions) by using their existing Workday user account.
    [b] [/b]
    Want to know more about us and your future colleagues[i]? [/i]You can watch these videos: [url=]Aalto University - Towards a better world[/url], [url=]Aalto People[/url][i] , [/i]and [url=]Shaping a Sustainable Future[/url].

    [b]About Finland[/b]
    [b] [/b]
    Finland is a great place for living with or without family - it is a safe, politically stable and well-organized Nordic society. Finland is consistently ranked high in quality of life and was just listed again as the happiest country in the world:  [url=][/url]. For more information about living in Finland:  [url=][/url]

    More about Aalto University:
    [url=]  [/url]

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