Title: Phenotype predictions using machine learning and ultra-high resolution microbiomics
We are looking for international candidates for a ESR PhD (ESR10) under the PEST-BIN project. The PhD work will take place at Clinical Microbiomics in Copenhagen and the PhD enrollment is via The Technical University of Denmark (DTU).
- Build a framework for prediction of host phenotypes or microbiome characteristics using machine learning, integrating ultra-high resolution microbiomics and clinical information.
- Build a framework for extracting detailed mechanistically insight from ultra-high resolution microbiomics associations.
Approach and expected results:
Clinical Microbiomics has deep-sequenced shotgun microbiome data from more than 20,000 human gut microbiome samples and has an array of metadata describing the host phenotype and sample condition. The metadata and extracted features from these datasets will be used as training and test set for machine learning algorithms. Moreover, Clinical Microbiomics has an established framework for ultra-high resolution microbiomics profiling, which uses SNV-level within species diversity to infer phylogenetic relationships among the populations of different samples. We will expand the framework to include additional association statistics and include additional features. The framework will expand on ancestral reconstruction to facilitate functional dissection of phylogenetic associations.
Candidates must be an ‘early stage researcher’ with experience from microbiome bioinformatics and machine learning and cannot have studied or worked in Denmark for more than 12 month within the last 3 years.
Please apply here before end of 2020.
Additional information about PEST-BIN project and PhDs can be found here: