PhD Student 100%
Universität Bern
Date de publication :
12 novembre 2024Taux d'activité :
100%- Lieu de travail :Bern
Department for BioMedical Research (DBMR), Bern
Start of employment: by agreement
temporary employment
Next-generation sequencing has great potential for clinical applications. Its ultimate promise is to provide personalized treatment recommendations for each patient. The research group of Dr. Matúš Medo studies algorithms for data generated by next-generation sequencing (genomics, transcriptomics, and proteomics).
Tasks
In our recent paper (https://rdcu.be/dYS4q), we documented important limitations of the available tools for signature analysis. We are now looking for applicants who will develop new algorithms specifically designed to overcome the identified shortcomings. These algorithms will be implemented as software packages that will improve and simplify the analysis of mutational signatures for the broad community of researchers and other practitioners. This will help to effectively use the costly sequencing data and thus enable discoveries and therapeutic decisions that would otherwise be impossible.
The chosen candidate will also perform state-of-the-art computational analyses of genomic profiling data to reveal deficiencies in DDR pathways in cohorts of head and neck squamous cell carcinoma patients from Inselspital, Bern. This will include DDR-related mutational signatures and homologous recombination deficiency scores. By combining this analysis with an in vitro evaluation of the efficacy of therapies targeting specific molecular players of DDR, this project will bridge the gap between genomic analysis and translation of research into clinical testing.
Requirements
We are looking for applications from outstanding candidates who hold an MSc. degree in bioinformatics or a related field. Applicants should have strong analytical skills, programming experience (Python and R), and fluency in English. Previous exposure to genomic analyses is of advantage. The applicants should be able to work independently as well as in a team, have critical thinking, good organizational skills, and a deep interest in research.
We offer
Application and contact
Your application should include a short letter of interest, curriculum vitae, a reference letter, university transcripts and certificates, your master thesis and (optional) relevant research papers. Send your application as a single PDF file to E-Mail schreiben.
Contact
Universität Bern