Bioinformatics PhD project: Computational methods for detection of cancers and their mutational imprints from sequencing of blood cell-free DNA
Call for a fully funded PhD position within cell-free DNA bioinformatics at the Dep. of Molecular Medicine (MOMA) and Dep. of Clinical Medicine, Aarhus University.
Blood cell-free DNA (cfDNA) is emerging as an important biomarker in cancer. Several studies have already demonstrated how it can both be used to determine whether cancer is present in blood or not, and act as a “liquid tumour biopsy”, which makes it possible to investigate the mutational profile of a tumour.
Sequencing is becoming the dominant approach for analysing cfDNA, yet finding signals of cancer let alone specific mutational events is difficult. First, because every tumour fragment is typically outnumbered by thousands of “background” fragments. Second, because technical artifacts originating e.g. from partial degradation of DNA may look a lot like real mutations.
In this PhD position, you will create new computational methods that combine classical statistical models with modern machine learning (e.g. neural nets) for finding those cancer “needles” in the blood “haystack”. You will both work on developing statistical models for determining ctDNA load and variants from whole-genome sequencing of cfDNA as well as methods for deep, targeted sequencing data.
Together with our collaborators at MOMA, we will apply the developed models to cfDNA-seq data from thousands of patients aiming at improving cancer care – from early detection in the screening context over relapse detection to finding mutations for guiding treatment. You will become part of the Danish National Center for Circulating Tumor DNA Guided Cancer Treatment (www.ctdna.dk), where you will interact with ctDNA minded experimentalists, clinicians and bioinformaticians from across Denmark.
You will be working at the Department of Molecular Medicine (MOMA), Department of Clinical Medicine at the Faculty of Health, Aarhus University. MOMA offers a vibrant and unique interdisciplinary research environment with several experimental and informatics groups focusing on translational cancer research powered by genomics. You will be a member of Tenure-track Assistant Prof. Lasse Maretty’s newly established research group at MOMA, which operates at the intersection between statistics, machine learning and genomics. You will also be supervised by Associate Prof. Søren Besenbacher, who will act as your formal PhD supervisor, as well as Filip Garrett Vieira at Rigshospitalet.
- You hold – or soon graduate with – a Master’s degree within bioinformatics, statistics, computer science or a related discipline.
- Proficiency in at least one programming language is required.
- Experience with handling of genomics data is advantageous.
- Knowledge about or strong interest in statistical modelling is advantageous.
- Knowledge about cancer biology and cell-free DNA is advantageous.
- Proficiency in both oral and written English is required.
How to apply
Please submit your application via this link. Application deadline is 1 May 2021 23:59 CET. Preferred starting date 1 July 2021.
For information about application requirements and mandatory attachments, please see our application guide.
All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.