Basel, Basel, Switzerland
Bioinformatician and data analyst dedicated to developing and applying bioinformatic and machine learning algorithms on genetic and epigenetic data to improve medical diagnosis of cancer.
- Combining and expanding open source (bio-) informatic tools, such as Linux, bash, R, Bioconductor and Python for curation and analysis of genome, transcriptome and epigenetic NGS and array data in the context of cancer classification and diagnosis. - Advancing wetlab and bioinformatic methods for methylome analysis. - Mantaining and advancing wetlab and IT infrastructure for methlyome analysis. - Bioinformatic support for diagnosis of brain cancer types.
Key responsibilities: • Supporting customer in using and expanding a Virtual Machine for running Archer Analysis software locally. • Customer support with (Linux) command to adjust the System to customer needs. • Assist Customer in interpretation of next generation sequencing data from Illumina and Ion Torrent platform • Helping customers in solving issues and trouble shooting • Escalating issues at customer sites to the Archer Analysis development team • Improving the documentation of Archer Analysis software and it’s extensions. • Conduct internal and remote Archer Analysis training in data analysis for customers.
Key responsibilities: • Analyzing next generation sequencing RNA and exome data. • Determination of new point mutations indicative for Malignant Hyperthermia. • Establishing an analysis pipeline for the identification of mutations in patient sample data. • Experimental design. Major achievements: • Establishing end to end analysis pipelines for the determination of indication specific SNP starting with Next Generation Sequencing fastq files. • Identification a set of new rare point mutations indicative for Malignant Hyperthermia in genes expressed in muscle.
Key responsibility: • Analyzing Next Generation Sequencing data with focus on RNA-Seq. • Data analysis using R, Rstudio, Bioconductor, Python, Linux programs and command line tools on the sciCORE High Performance Cluster. • Establishing and evaluating new bioinformatic tools. Major achievements: • Identification of multiple bioinformatic methods for determining the level of RNA degradation of RNA samples using RNS -seq data. • Independent bioinformatic verification of one method for the estimation of RNA degradation.
Key focus: • Understanding customer goals and analyzing their needs. • Evaluating established laboratory processes and methods. • Identifying steps / methods potentially affecting reproducibility of experimental series. • Data analysis. • Guiding the optimization of routines and equipment to meet customer goals.