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    PhD Student in implementation of autonomous epitaxy combining experiments, simulations and machine learning 100%

    Paul Scherrer Institut

    Paul Scherrer Institut, CH-5303 Würenlingen

    Grossunternehmen

    2000 Angestellte (Schweiz)
    0 Angestellte (global)

    Temporär: Nein Pensum: 100%
    CH-5303 Würenlingen Sprache: en

    Original Inserat / Bewerben

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    The Paul Scherrer Institute PSI is the largest research institute for natural and engineering sciences within
    Switzerland. We perform cutting-edge research in the fields of future technologies, energy and climate, health
    innovation and fundamentals of nature. By performing fundamental and applied research, we work on sustainable solutions
    for major challenges facing society, science and economy. PSI is committed to the training of future generations.
    Therefore, about one quarter of our staff are post-docs, post-graduates or apprentices. Altogether, PSI employs 2300
    people.
    For the Thin Films and Interfaces Group and the Materials Software and Data Group we are looking for a

    PhD Student in implementation of autonomous epitaxy combining experiments, simulations and machine learning

    Your tasks

    This project aims to develop, implement, and validate a fully autonomous route for the optimization of the growth of
    epitaxial oxide thin films using physical vapor deposition. Multiple in situ characterization techniques will be
    employed, monitoring quality indicators of the films while they are growing and allowing for the live tuning of the
    growth parameters.
    You will be responsible for developing a hardware-software interface for autonomous thin film growth (including both
    the operation of the chamber and the monitoring of the in situ techniques). You will combine these interfaces with
    machine learning approaches, exploring optimization algorithms to control the structural and chemical properties of the
    resultant thin films, aiming at determining the parameters for crystalline and stoichiometric epitaxial growth. The
    resulting code that you develop, and implement will be integrated into an autonomous platform to drive the search for
    the ideal growth conditions. Subsequently, you will demonstrate and validate the developed models through the
    autonomous growth optimization of functional oxide thin films. The infrastructure, the methods and the collected data
    will be published in peer reviewed articles.
    You will be enrolled in the Materials Science and Engineering Doctoral program at EPFL, from which you will receive
    your PhD title. The doctoral candidature will involve in-person coursework at EPFL in Lausanne.

    Your profile

    Candidates are sought with a background in the physical sciences or engineering, alongside a passion for programming.
    Candidates are expected to show excellent work ethics and to feel at home working in teams. Female candidates are
    strongly encouraged to apply.
    Requirements for the candidates are:

    - Master’s degree in Physics, Chemistry, Engineering or Materials Science
    - Strong programming skills (ideally in Python, but advanced knowledge of other programming languages will also be
    considered)
    - Strong motivation for materials science and discovery, for working in a team and a passion for automation of
    repetitive tasks
    - Excellent communication skills in written and spoken English (knowledge of German is a plus but not required)
    - Optional, desirable but not required: Hands-on experience with physical vapor deposition techniques, vacuum systems
    and/or pulsed excimer lasers
    - Optional, desired but not required: Experience with machine-learning techniques and data analysis

    We offer

    Our institution is based on an interdisciplinary, innovative and dynamic collaboration. You will profit from a
    systematic training on the job, in addition to personal development possibilities and our pronounced vocational
    training culture. If you wish to optimally combine work and family life or other personal interests, we are able to
    support you with our modern employment conditions and the on-site infrastructure.
    For further information, please contact Dr Nikita Shepelin, email nikita.shepelin@psi.ch or Dr Giovanni Pizzi, email
    giovanni.pizzi@psi.ch.
    Please submit your application online by 16 February 2025 (including addresses of referees) for the position as a PhD
    Student (index no. 3704-00).
    Paul Scherrer Institute, Human Resources Management, Serdal Varol, 5232 Villigen PSI, Switzerlandwww.psi.chApply now

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