DTU PhD scholarship in Laser physics, Bayesian filtering, Machine learning jobs

    DTU PhD scholarship in Laser physics, Bayesian filtering, Machine learning jobs

    Laser physics, Bayesian filtering, Machine learning jobs – PhD scholarship in Noise Characterization of Lasers and Frequency Combs using Machine Learning, at DTU Fotonik, Technical University of Denmark


    Deadline to Apply

    May 26, 2021 (23: 59 GMT +1)


    Overview

    PositionPhD Position
    No. of Position(s)1
    Research Area– Laser physics
    – Machine learning
    – Bayesian filtering
    – Optical communication systems
    ScholarshipAccording to standard norms
    WorkplaceDTU Fotonik
    Technical University of Denmark
    Contract Period3 Years
    Starting dateAs soon as possible

    Qualifications

    You must have a two-year master’s degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master’s degree.

    You are expected to have experience with laser physics, machine learning, Bayesian filtering and optical communication systems.

    Preference

    • Good understanding of adaptive filtering techniques (Kalman and Wiener filtering)
    • Good understanding of digital signal processing (signal analysis, power spectrum estimation, time-series analysis)
    • Good theoretical understanding of linear algebra with special focus on singular value and eigenvalue decomposition methods
    • Good understanding of numerical methods for optimization
    • Experience with machine learning techniques (expectation maximization algorithms, neural networks, Guassian processes, etc.)
    • Experience using MATLAB, Python or similar
    • Experience with software for version control such as git
    • Ability to work independently, to plan and carry out complicated tasks
    • Good communication skills in English, both written and spoken
    • Innovative skills and the ability to generate new ideas

    Responsibilities

    This Ph.D. project will explore the latest advances within machine learning to enable ultra -broadband and -sensitive noise characterization of laser sources and frequency combs. A machine learning based framework for joint tracking of amplitude and phase noise will be developed. The framework will rely on Bayesian filtering which offers record sensitivity and operation at to the quantum limit. The project will also focus on learning the corresponding state-space models for tracking amplitude and phase noise. The focus will be on low-complexity solutions that are feasible for real-time implementation. The project will cover both algorithm development as well as experimental implementations. 
    Your work will includes research into novel methods for noise characterization of lasers and frequency combs. Specifically you will focus on the following areas:

    • Bayesian filtering framework for joint tracking of amplitude and phase noise of lasers and frequency combs 
    • Multi-layer neural networks for learning the evolution of amplitude and phase noise from the measurements data
    • Relating the amplitude-phase noise correlation matrices to comb’s physical parameters such as timing jitter, carrier envelope frequency offset and power supply noise
    • Building experimental set-ups for noise characterization of laser and frequency combs
    • Maintenance  of the GitHub repository for the developed code
    • Organising and managing joint experiments with the collaboration groups

    How to Apply?

    To apply, please open the link “Apply online”, fill out the online application form, and attach all your materials in English in one PDF file

    Documents Required

    • A letter motivating the application (cover letter)
    • Curriculum vitae
    • Grade transcripts and BSc/MSc diploma
    • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)

    About Research project

    The objective of the proposed PhD project project is to develop novel machine learning based methods for noise characterization of lasers and optical frequency comb. The start date is flexible but preferably as soon as possible. The project is interdisciplinary and will cover topics within the field of laser physics, machine learning, quantum optics and optical communication. The project will be carried out in Machine Learning in Photonic Systems (M-LiPS) group. The group has a strong track record and and industry collaboration in the application of machine learning techniques to optical communication and measurements systems in general. A close collaboration with NKT Photonics (leaders in ultra-low noise laser sources) and the University of California Santa Barbara (Prof. John E. Bowers group) is envisioned within the project. 

    About DTU Fotonik

    DTU Fotonik has 210 employees with competences in optics and is one of the largest centres in the world based solely on research in photonics. Research is performed within optical sensors, lasers, LEDs, photovoltaics, ultra-high speed optical transmission systems, bio-photonics, nano-optics and quantum photonics.

    Note

    • The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union
    • If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark

    Inquiries

    Associate Professor Darko Zibar
    Email: dazi@fotonik.dtu.dk

    Official advertisement

    PhD scholarship in Noise Characterization of Lasers and Frequency Combs using Machine Learning

    Post expires at 8:59am on Thursday May 27th, 2021 (GMT+9)