PhD position in Machine Learning Model Development for Electronic Scale Inverse Design of Enzymatic Catalysts

The section of Cognitive Systems at DTU Compute, Technical University of Denmark (DTU) is looking for an outstanding candidate for a PhD position on machine learning method development aimed at molecular science. The research position is part the research projectDEep LearnIng Green cHemical caTalysis (DELIGHT) funded by DFF which brings together researchers from DTU Energy, DTU Compute and Department of Chemistry, University of Copenhagen.r

In this project we will develop a deep learning framework for reverse engineering of biocatalysts and pave the way for artificial (electro)catalysts capable of producing green fuels and chemicals; specifically an artificial Nitrogenase catalyst for production of ammonia.

Project description
In the DELIGHT project, we take a data-centric approach to learn the complex electronic interplay between enzyme and the cofactors using machine learning generated datasets of biological and artificial enzymatic catalysts and develop a deep inverse generative model for enzyme design. The enzyme dictate the catalytic effects at the cofactor structurally and electronically. Small changes in the surrounding protein can radically change the properties directly related to the electronic interaction.

We will develop deep generative models that learn electronic structure fingerprints of the enzymes that are critical towards catalytic effects.  We will use discovered electronic descriptors to mimic nature's best enzymes via a conditional generation framework that tailors the electronic structure encoding for the catalytic properties in IL- nanocluster composites. Electronic charge density will be used for a continuous design space for inverse design. The project will combine concepts from the enzymatic catalysis theory, conditional deep generative models with 3D data coming from electronic structure of materials.

This PhD project will be carried out in tandem with two other PhD projects at DTU Energy and Department of Chemistry, University of Copenhagen. The main focus of this position is on methods development in deep learning based generative modelling for learning distributions over features embedded in Euclidian space. 

Qualifications
You will have obtained excellent grades in your Bachelor and Master educations. A solid background in machine learning theory and software development is required. Moreover, knowledge of molecular and materials science through university level courses or project work is preferred. Furthermore, you should be highly motivated and willing to work in a team. Good communication skills in both spoken and written English, are a requirement. 

Approval and Enrollment of PhD Students
The scholarship is subject to academic approval, and the candidates will be enrolled at the Compute PhD School at DTU. For information about the general requirements for enrolment and the general planning of the PhD study programme, please see the DTU PhD Guide .

Assessment
Professor Ole Winther, Professor Tejs Vegge, Professor Jan H Jensen and Researcher Arghya Bhowmik will assess the applicants.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and terms of employment
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. The period of employment is for three years. The position is available from September 2021.

You can read more about career paths at DTU here .

Further information
If you need further information concerning these positions, please contact Prof. Ole Winther at [email protected] or Researcher Arghya Bhowmik at [email protected] .

You can read more about DTU Compute www.compute.dtu.dk/english . 

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark . 

Application procedure
Your complete online application must be submitted no later than31 July 2021(Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. 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. The file must include:

• 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 )

You may apply prior to obtaining your master's degree but cannot begin before having received it.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Compute
DTU Compute is a unique and internationally recognized academic environment spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard—producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 12,900 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.