About PhD Position on Deep Learning and Molecular Modeling for Optimal Catalyst Materials

Faculties der Natuurw., Wiskunde en Informatica
PhD position
Deadline: 31/12/2021

Are you interested in developing cutting-edge machine learning methods to design new molecules, materials and chemical processes that help to solve the global warming crisis? We are looking for a PhD candidate to investigate how to combine data from quantum chemical calculations, molecular simulations, and experimental catalysis to “inverse design” optimal catalyst materials for CO2 conversion.

Using CO2 as a feedstock for the industrial production of chemicals is an appealing approach to prevent greenhouse gas emissions. However, conversion of CO2 into useful chemicals and fuels requires efficient catalysts. Design of catalytic materials and processes is challenging due to the large number of design parameters. The aim of this project is to develop a deep probabilistic programming framework to train models from computational and experimental data and to infer optimal catalyst materials and process conditions, given a set of desired properties such as reaction rates, selectivity, stability, and so forth.

This position is on a collaborative project by computational chemist Dr. Bernd Ensing (HIMS/AI4Science Lab), machine learning experts Prof. dr Max Welling and Prof. dr Jan-Willem van de Meent (IvI, AMLAB), experimental chemist/chemical engineer Dr. Shiju Raveendran (HIMS, Catalysis Engineering), and the UvA Data Science Center.

What are you going to do

You will carry out research in the areas of geometric deep learning, probabilistic programming, and molecular modeling, with applications in heterogeneous catalysis. Through this research you will develop new methods for discovering chemical structure-property relationships, learning features for chemical transformations, generating molecular structures, and meta-learning for sampling chemical space given sparse data. 

In this project, you will:

  • be part of an exciting multidisciplinary community of people interested in developing and applying data-driven solutions for scientific discovery;
  • develop deep probabilistic methods to generate optimal molecular structures given desired properties and specifications;
  • use quantum chemistry calculations and molecular simulations of catalytic materials and chemical reactions for analysis and data generation;
  • become active in the research community and collaborate with other institutes and/or companies that are part of the project;
  • publish and present work regularly at international conferences, workshops, and journals;
  • assist in teaching activities and in supervising Bachelor and Master students.

What do we require

  • A recent Master’s degree in Computer Science, Artificial Intelligence, Data Science, (Computational) Chemistry, (Molecular) Physics, or closely related field;
  • good programming skills preferably in Python, and proficiency with one or more deep learning frameworks;
  • strong analytical and technical skills;
  • willingness to work and collaborate in an open, inclusive, team-spirited manner in the laboratories of CompChem, AI4Science, AMLAB, and/or DSC;
  • willingness to perform a secondment in the catalyst engineering group and learn relevant aspects of heterogeneous catalysis, catalyst materials, experimental data acquisition;
  • fluency in oral and written English and good presentation skills.

Questions

Do you have questions about this vacancy? Or do you want to know more about our organisation? Please contact:

  • Dr. Bernd Ensing, Associate Professor Computational Chemistry; AI4Science Lab
  • T. + 31 (0)20 525 7538 

For more information, see also the websites of the involved research groups:

The Van ‘t Hoff Institute for Molecular Sciences (HIMS) is one of eight institutes of the University of Amsterdam (UvA) Faculty of Science. HIMS performs internationally recognized chemistry and molecular research, curiosity driven as well as application driven. This is done in close cooperation with the chemical, flavor & food, medical and high-tech industries. Research is organized into four themes: Synthesis & Catalysis, Analytical Chemistry, Computational Chemistry and Molecular Photonics.

Are you interested in developing cutting-edge machine learning methods to design new molecules, materials and chemical processes that help to solve the global warming crisis? We are looking for a PhD candidate to investigate how to combine data from quantum chemical calculations, molecular simulations, and experimental catalysis to ‘inverse design’ optimal catalyst materials for CO2 conversion.

Using CO2 as a feedstock for the industrial production of chemicals is an appealing approach to prevent greenhouse gas emissions. However, conversion of CO2 into useful chemicals and fuels requires efficient catalysts. Design of catalytic materials and processes is challenging due to the large number of design parameters. The aim of this project is to develop a deep probabilistic programming framework to train models from computational and experimental data and to infer optimal catalyst materials and process conditions, given a set of desired properties such as reaction rates, selectivity, stability, and so forth.

This position is on a collaborative project by computational chemist Dr. Bernd Ensing (HIMS/AI4Science Lab), machine learning experts Prof. dr Max Welling and Prof. dr Jan-Willem van de Meent (IvI, AMLAB), experimental chemist/chemical engineer Dr. Shiju Raveendran (HIMS, Catalysis Engineering), and the UvA Data Science Center.

What are you going to do

You will carry out research in the areas of geometric deep learning, probabilistic programming, and molecular modeling, with applications in heterogeneous catalysis. Through this research you will develop new methods for discovering chemical structure-property relationships, learning features for chemical transformations, generating molecular structures, and meta-learning for sampling chemical space given sparse data.

You will:

  • be part of an exciting multidisciplinary community of people interested in developing and applying data-driven solutions for scientific discovery;
  • develop deep probabilistic methods to generate optimal molecular structures given desired properties and specifications;
  • use quantum chemistry calculations and molecular simulations of catalytic materials and chemical reactions for analysis and data generation;
  • become active in the research community and collaborate with other institutes and/or companies that are part of the project;
  • publish and present work regularly at international conferences, workshops, and journals;
  • assist in teaching activities and in supervising Bachelor and Master students.

What do we require of you

  • A recent Master’s degree in Computer Science, Artificial Intelligence, Data Science, (Computational) Chemistry, (Molecular) Physics, or closely related field;
  • good programming skills preferably in Python, and proficiency with one or more deep learning frameworks;
  • strong analytical and technical skills;
  • willingness to work and collaborate in an open, inclusive, team-spirited manner in the laboratories of CompChem, AI4Science, AMLAB, and/or DSC;
  • willingness to perform a secondment in the catalyst engineering group and learn relevant aspects of heterogeneous catalysis, catalyst materials, experimental data acquisition;
  • fluency in oral and written English and good presentation skills

Our offer

A temporary contract for 38 hours per week for the duration of four years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of four years). This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.

The gross monthly salary based on full-time employment (38 hours per week) ranges from €2,434 to €3,111 (scale P). This is exclusive 8% holiday allowance and 8,3% end-of-year bonus. The starting salary will be based on qualifications, expertise and relevant experience. The Collective Labour Agreement of Dutch Universities is applicable.

The UvA offers excellent possibilities for further professional development and education.

About us

The Van ‘t Hoff Institute for Molecular Sciences (HIMS) is one of eight institutes of the University of Amsterdam (UvA) Faculty of Science. HIMS performs internationally recognized chemistry and molecular research, curiosity driven as well as application driven. This is done in close cooperation with the chemical, flavor & food, medical and high-tech industries. Research is organized into four themes: Synthesis & Catalysis, Analytical Chemistry, Computational Chemistry and Molecular Photonics.

To work at the UvA is to work in a discerning, independent, creative, innovative and international climate characterized by an open atmosphere and a genuine engagement with the city of Amsterdam and society. Here you can read more about working at the UvA.

Job application


Do you recognize yourself in the job profile? Then we look forward to receiving your application 31 December 2021. 

Applications in .pdf should include:

  • a motivation letter, describing your research interests and your reasons applying to this position;
  • a detailed curriculum vitae (cv);
  • copies of (or links to) samples of your writing (Master’s thesis, term paper, publications);
  • the names of two references.

The UvA is an equal-opportunity employer. We prioritize diversity and are committed to creating an inclusive environment for everyone. We value a spirit of enquiry and perseverance, provide the space to keep asking questions, and promote a culture of curiosity and creativity.

No agencies please

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