Few Postdoc Positions – Machine Learning Chemistry, Computational Chemistry, Catalysis

    Few Postdoc Positions in Machine Learning Chemistry, Computational Catalysis, Computational Chemistry, Chemical Physics is available at the Department of Physics and Astronomy, Aarhus University, Denmark

    Postdoc Positions in Machine Learning for Catalysis and Chemical Physics

    Deadline to Apply

    Apr 20, 2021 (GMT+1)


    Postdoc Position

    No. of Position(s)


    Research area

    • Physics
    • Chemistry
    • Nanoscience
    • Computer science


    According to Standard Norms


    Dept. of. Physics and Astronomy

    Contract period

    3 Year
    Starting date is 1 June 2021 or sometime thereafter.


    Mie Andersen
    Bjørk Hammer
    Please use as e-mail subject: “postdoctoral position 21”.


    • PhD degree in physics, chemistry, nanoscience, computer science or equivalent.
    • Previous experience with machine learning methods and/or first principles energy calculations in physical chemistry is required.
    • Experience with programming in python is highly desired.

    Responsibilities/Job Description

    Machine Learning for Catalysis

    • In this project, the successful candidate will contribute to the development of a computational framework based on active learning to guide the search for materials that catalyze the conversion of CO2 to methanol at low temperatures.
    • In recent work, Mie Andersen’s group has developed machine learning models for the prediction of catalytically relevant parameters such as adsorption energies for a wide range of molecules and active site motifs at metal and oxide catalysts.
    • The predictive models can, once trained, replace expensive first-principles calculations and provide direct input to thermodynamic or microkinetic models of catalytic activity and selectivity.
    • The postdoc will be introduced to these methods and is expected to further develop them into an active learning framework that, among others, will include the use of uncertainty estimates to carry out global sensitivity analysis and uncertainty quantification of microkinetic models
      Machine Learning for Chemical Physics
    • In this project, the successful candidate(s) will identify and develop machine learning techniques that may speed up first principles calculations of equilibrium structures and reaction pathways in chemical physics. In recent years, Bjørk Hammer’s group has developed a number of techniques for global optimization (see: https://gofee.au.dk).
    • One method, GOFEE, does its structural search in a model potential using Gaussian Process Regression and is guided by Bayesian statistics to perform occasional sanity checks with full density functional theory (DFT) calculations. Another method, ASLA (see: https://asla.au.dk), does self-training of image recognition for neural network agents that interact with a DFT program.
    • The postdoc(s) will be introduced to these methods and be expected to develop their own improvements and to apply these in the search for the reactive state of matter ranging from interstellar dust clouds to industrial heterogeneous catalysts.

    How to Apply?

    To apply, please click APPLY ONLINE button mentioned above.

    Documents required

    • A curriculum vitae
    • Degree certificate
    • A complete list of publications
    • A statement of future research plans and information about research activities
    • Teaching portfolio and verified information on previous teaching experience (if any)
      Guidelines for applicants can be found here.

    Other Benefits

    • Aarhus University offers a broad variety of services for international researchers and accompanying families, including relocation service and career counselling to expat partners
    • Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU 


    • Salary depends on seniority as agreed between the Danish Ministry of Finance and the Confederation of Professional Associations
    • All interested candidates are encouraged to apply, regardless of their personal background. Research activities will be evaluated in relation to actual research time. Thus, we encourage applicants to specify periods of leave without research activities, in order to be able to subtract these periods from the span of the scientific career during the evaluation of scientific productivity

    Other Postdoctoral Positions

    Post expires at 8:59am on Wednesday April 21st, 2021 (GMT+9)