PHD STUDENT, ENZYME RESEARCH, NOVOZYMES

What if you could work for a cause, not just a company?
Novozymes is the global market leader in biological solutions. We help build better lives. Together with our customers, partners and the global community, we use our innovative thinking and passion for science to boost industries and make everyday products more sustainable for the good of the planet. As the world’s leading provider of industrial enzymes and microorganisms, our bio-innovation enables higher agricultural yields, low-temperature washing, energy-efficient production, renewable fuel and many, many other biological solutions that the world can benefit from today and in the future. We call it Rethink Tomorrow. 

Project Description 
Enzyme discovery and engineering are extremely challenging due to the enormous protein sequence space and the often demanding- application conditions under which the enzyme must function. However, we are witnessing an explosion of structural and experimental data that help create accurate models, that can assist in efficiently sampling of sequence space and to predict relevant properties of proteins. The aim of the project is to use machine learning to accelerate protein engineering, by building an AI-centric protein design framework to reduce the experimental cost of directed evolution. The successful candidate will develop novel supervised machine learning approaches, trained on in-house experimental data, to predict different physical and chemical properties of proteins.

Predictions will be assessed and validated using data derived from high-throughput screening and directed evolution experiments. This is an exceptional opportunity to combine research in machine learning (e.g. Bayesian Optimization, Representation Learning) to real-world challenges, to pushing the state of the art in protein design. The project will build on collaborative interaction between three partners: 1) Department of Bioinformatics and Design at Novozymes (Pengfei Tian, Jesper Salomon), 2) Machine Learning section at the Department of Computer Science, University of Copenhagen (Wouter Boomsma), and the group of Debora Marks at Harvard Medical School.

Welcome to Enzyme Research
You will be joining a team of dedicated scientists with competences in molecular biology, structural bioinformatics, molecular simulation, enzyme discovery, deep learning and natural language processing. We bring these competences together to discover and engineer new enzymes that help our customers optimize their processes, save energy, reduce chemicals and lower the overall environmental impact.

In this role you’ll make an impact by:

• Follow and share public research within the field of protein design and machine learning
• Drive the research and development of AI guided sampling methods using machine learning
• Success of your research will accelerate the enzyme engineering process in Novozymes to discover more robust and active enzymes

Qualifications  
Candidates should have a two-year master's degree or a similar degree equivalent to a two-year master's degree. The master's degree should be in at least one of the following areas: computer science, bioinformatics, physics, chemistry, computational science, statistics, applied mathematics, engineering, or equivalent academic qualifications.

Preference will be given to candidates who have:

• Passion for machine learning, with experience in both deep learning and probabilistic methods like Gaussian Processes
• Good knowledge in statistics, data analysis tools and libraries
• Strong computer programming skills e.g. Python, R, or other programming languages relevant for computational work
• Previous experience in bioinformatics, biochemistry, protein modelling and design is desirable, but not mandatory

To apply, please include:

• Cover Letter: motivation and background for applying for the PhD project.
• Curriculum vitae (CV) 
• Diploma and transcripts of records (BSc and MSc), list of publications (if any)
• Contact information (Name, address, telephone & email) of 1-3 professional referees

Employment:
The project is co-funded by InnovationFund Denmark. The position is available for a 3-year period. Start date is spring 2022. You will have access to expert knowledge within deep learning and data science. The project is jointly supervised by Senior Data Scientist Pengfei Tian (pti@novozymes.com), Science Manager Jesper Salomon (jrsx@novozymes.com) and Associate Professor Wouter Krogh Boomsma (Copenhagen University (wb@di.ku.dk), as well as Associate Professsor Debora Marks (Harvard University, debbie@hms.harvard.edu). During the PhD, the student is encouraged to visit an external research institution (e.g. Harvard Medical School) for a few months.

Location
This job will be located at Kgs. Lyngby, Denmark. Are you passionate about making a sustainable impact, and do you see yourself in this position? Then unlock your passion and apply today!
Application deadline: 1st of February 2022. Contact details: Sr. Department Manager Peter Fischer Hallin (pfha@novozymes.com).

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