New DDSA Fellow will improve the predictions of protein variants using machine learning methods
Richard Michael is one of the first ten candidates to receive the prestigious PhD fellowship from the Danish Data Science Academy (DDSA). He will be conducting research within protein engineering at the Machine Learning section at Department of Computer Science, University of Copenhagen (DIKU) with Associate Professor Wouter Boomsma as supervisor.
Protein engineering has a wide range of applications from biotechnology to drug discovery. In essence, it is a search problem, where the goal is to find mutations, or variants, that improve a particular trait of a protein, for instance its stability or function. In his project 'Principled Bayesian Optimization and scientific ML for Protein Engineering', Richard will investigate and develop new methods to improve the predictions of protein variant candidates with respect to a desired function.
The space of possible proteins is vast, and experimentally probing all relevant candidates is intractable. The design of proteins with the intended properties entails a vast discrete search-space and while there are computational representations and experimental observations available, there is a lack of methods to adequately combine all available information. Richard will use state-of-the-art probabilistic optimization and propose a novel machine learning method – Principled Bayesian Optimization on latent representations - with the aim of finding better candidates using fewer experimental resources.
Joins DIKU’s Machine Learning section
The project is a collaboration between the Machine Learning in Biology group at the Department of Computer Science, University of Copenhagen (DIKU), and the Department of Chemistry under joint supervision at the University of Copenhagen. Richard will therefore be an affiliate of the Machine Learning Section at DIKU and will be supervised by Associate Professor Wouter Boomsma.
– I am very happy that we managed to get one of the first of these fellowships to DIKU and look forward to working with Richard on his project, says Wouter Boomsma, supervisor and Associate Professor in the Machine Learning section at DIKU.
One of the first to receive DDSA fellowship
The Danish Data Science Academy is a new national initiative that supports data science activities in Denmark, including travel grants, funding for inviting academic visitors and organizing scientific meetings. They also provide funding for postdocs and 10 annual Ph.D. fellowships. Richard is one of the first ten PhD students to receive the fellowship.
– I am thrilled about the opportunity that the DDSA provides and look greatly forward to research at the intersection of Machine Learning, probabilistic optimization, and its integration into experimental design together with our collaborators, concludes PhD Fellow Richard Michael.
Richard holds a bachelor’s degree in Cognitive Science from the University of Osnabrück in Germany and a master’s degree in Bioinformatics in Computer Science from the University of Copenhagen.
Learn more about his project in the video below.
About Danish Data Science Academy
The Novo Nordisk Foundation and the VILLUM FOUNDATION award a total combined grant of DKK 184.3 million to the Danish Data Science Academy, which will support and initiate new initiatives for Danish research institutions and tech companies. Primarily within training of experts and interdisciplinary collaboration, two crucial areas for Denmark to realize its potential within data science.
The main objective of the DDSA Fellowship Programme is to attract and educate excellent PhD students and postdocs within data science, achieve scientific excellence and impact, while simultaneously extending the application of data science in relevant scientific domains.
More information available here.
Contact
Richard Michael
PhD Fellow
Department of Computer Science
University of Copenhagen
richard.michael@di.ku.dk
Wouter Boomsma
Associate Professor
Department of Computer Science
University of Copenhagen
wb@di.ku.dk
Rebekka Grage Rasmussen
Communication Consultant
Department of Computer Science
University of Copenhagen
rgr@di.ku.dk