PhD Position available
The Computational Metabolomics for Systems Biology lab, part of the Metabolomics Interdisciplinary Lab (MIL@b) and associated with the Omic Sciences Unit of Eurecat - Technology Centre of Catalonia, seeks a PhD candidate to develop new methods for metabolomics data analysis. This involves analyzing biological samples using mass spectrometry-based metabolomics workflows and processing and analyzing the data via computational methods, thus being able to study fundamental questions from a systems biology perspective. The candidate will be enrolled in a University Rovira i Virgili PhD program and will carry out the main research activity School of Engineering (ETSE), Sescelades Campus (Tarragona, Catalonia, Spain).
The thesis will revolve around the use of computational solutions to streamline the mass spectrometry-based untargeted metabolomics workflow, to enable the annotation and identification of metabolites in biological samples.
Through our network of collaborators, the candidate will be involved in different collaborative projects, and he/she will also perform a secondment in a different institution for at least 3 months.
Key responsibilities:
- Use advanced statistical and signal processing methods for mass spectrometry-based untargeted metabolomics data interpretation.
- Analysis of metabolomics data using stable stable isotope labeling strategies.
- Development of algorithms for high-performance mass spectrometry imaging data processing.
- The application of machine learning and data mining strategies for metabolomics data analysis.
Requirements:
We are looking for a highly motivated graduate student with a B.Sc or M.Sc in (bio)informatics, bioengineering, biomedical engineering, biotechnology, or similar. The position requires solid programming skills in at least R, and an elemental knowledge of biostatistics and biochemistry. Knowledge of omics data analysis, particularly in metabolomics, is a plus. The candidate is expected to be a creative person and a team player with the capacity to work independently. Excellent writing skills in English are also needed.
The thesis will revolve around the use of computational solutions to streamline the mass spectrometry-based untargeted metabolomics workflow, to enable the annotation and identification of metabolites in biological samples.
Through our network of collaborators, the candidate will be involved in different collaborative projects, and he/she will also perform a secondment in a different institution for at least 3 months.
Key responsibilities:
- Use advanced statistical and signal processing methods for mass spectrometry-based untargeted metabolomics data interpretation.
- Analysis of metabolomics data using stable stable isotope labeling strategies.
- Development of algorithms for high-performance mass spectrometry imaging data processing.
- The application of machine learning and data mining strategies for metabolomics data analysis.
Requirements:
We are looking for a highly motivated graduate student with a B.Sc or M.Sc in (bio)informatics, bioengineering, biomedical engineering, biotechnology, or similar. The position requires solid programming skills in at least R, and an elemental knowledge of biostatistics and biochemistry. Knowledge of omics data analysis, particularly in metabolomics, is a plus. The candidate is expected to be a creative person and a team player with the capacity to work independently. Excellent writing skills in English are also needed.