Faculty of Health and Medical Sciences
University of Copenhagen

We are looking for a highly motivated and dynamic postdoc for a 4-year position, to commence 1st February 2024, or soon thereafter (flexible start date).

The postdoc will be linked to the ERC Consolidator project “STRUCTOMATIC” to study mutagenic and DNA repair processes operating in human cells, in particular those generating structural variation (SV, also known as genomic rearrangements) and their role in disease. We will combine diverse computational approaches based on artificial intelligence, evolutionary modelling, and long-read genome sequencing data analysis. The aim is to infer SV mutation risk and understand consequences of SVs on genetic disease, cancer, and other aging-associated disorders.

Information on the department can be found at: https://www.bric.ku.dk/

Our research

The Supek group is home to a highly interdisciplinary team, working at the intersection of genomics, molecular biology, and artificial intelligence. In our studies, we are striving for excellence and impact – we aim to do science that pushes the boundaries of human knowledge, and that benefits citizens health. The lab employs cutting-edge technologies in large-scale data analysis (cancer genomics, population genomics), DNA/RNA sequencing (e.g. Nanopore data generation and analysis), gene editing (e.g. Cas12a combinatorial disruption) and artificial intelligence (e.g. DNA and protein language models).

In addition to focus on high-impact research projects (e.g. ERC “HYPER-INSIGHT”, ERC “STRUCTOMATIC”), the Supek group also has a broad network of international collaborators across Europe (see e.g. EU Horizon consortia “DECIDER” and “LUCIA”, where we study ovarian and lung cancer genome evolution, respectively). The lab fosters a dynamic and inclusive atmosphere where excitement about science is valued. We are highly committed to mentoring and career development of PhD students, postdoctoral fellows, and other team members.

Your job

We invite the brightest minds in the world of bioinformatics to dive into the frontier of human genomics research using machine learning. As a part of our dynamic team, you'll be at the forefront of understanding structural variation (SV) mutations in the human genome, and their impact on disease risk and cancer evolution.

You will lead the charge in developing a computational framework based on DNA language models that comprehensively describes repetitive, structure-prone, difficult-to-replicate sequences, linking them with DNA fragility and with varied SV mutational risk features. This will be applied to long-read sequencing data (Nanopore, PacBio), drawing both on public genomic resources (cancer genomes, population genomes) and on genomes and transcriptomes generated in-house.

You will utilize cutting-edge deep learning methodologies (transformers, convolutional nets, autoencoders) to describe risk towards breakage and rearrangement in various loci of the human genome, based on the DNA sequence and on the epigenomic features. You will study the variation in local SV mutation risk across individuals, and link this with their inherited genetic background. This will elucidate the consequences of genetic variation in human populations on risk of acquiring pathogenic SV mutations in disease genes, particularly those driving cancer evolution. Your research will have broad-ranging implications to understanding DNA replication/repair mechanisms, human genome evolution, and genetic disease and cancer risk prediction.

Profile
We are looking for a highly motivated and enthusiastic scientist with the following competencies and experience:

Essential experience and skills:

• You have a PhD in genomics/epigenomics/transcriptomics, evolutionary biology, (bio)statistics or machine learning or related fields.
• You are experienced in various computational biology tools/databases, in statistical data analysis and visualization, and in writing code in at least one programming language.
• You have an active interest in understanding the biology of mutagenesis and DNA repair and its role in genetic disease, and in learning new bioinformatics and artificial intelligence approaches.
• Solid level of written and spoken English
• At least one first-author publication or preprint from your PhD and/or MSc work.

Desirable experience and skills:

• Experience with bioinformatics methods and tools for (a) genetic variant calling; and/or (b) mutational signature analysis; and/or (c) evolutionary modelling (tests for selection etc); and/or (d) long read sequencing analysis; and/or (e) neural networks.
• Background knowledge in fields related to biomedical genomics or DNA replication/repair or genome evolution or applied AI to omics data.
• Proficiency in R or Python, and genomics and machine learning libraries therein.
• Two or more first-author publications and/or preprints from your PhD and/or MSc work.

Place of employment

The place of employment is at the Biotech Research & Innovation Centre (BRIC), University of Copenhagen. We offer creative and stimulating working conditions in dynamic and an international research environment. Our research facilities include modern laboratories and high-performance computing infrastructure.

Terms of employment
The average weekly working hours are 37 hours per week.

The position is a fixed-term position limited to a period of 4 years. The starting date is 1st February 2024, or as soon as possible thereafter.

Salary, pension and other conditions of employment are set in accordance with the Agreement between the Ministry of Taxation and AC (Danish Confederation of Professional Associations) or other relevant organisation. Currently, the monthly salary starts at 36,412 DKK/approx. 4,880 EUR (October 2023 level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 17.1 % to your pension fund.

Foreign and Danish applicants may be eligible for tax reductions, if they hold a PhD degree and have not lived in Denmark the last 10 years.

The position is covered by the Job Structure for Academic Staff at Universities 2020.

Questions
For further information about the project and the postdoc position, please contact Prof. Fran Supek; [email protected]

Foreign applicants may find this link useful: www.ism.ku.dk (International Staff Mobility).

Application procedure
Your online application must be submitted in English by clicking ‘Apply now’ below. Furthermore, your application must include the following documents/attachments – all in PDF format:

1. Motivated letter of application (max. one page).
2. CV incl. education, work/research experience, language skills and other skills relevant for the position.
3. A certified/signed copy of a) PhD certificate and b) Master of Science certificate. If the PhD is not completed, a written statement from the supervisor will do.
4. List of publications and preprints. Please include summaries for up to 3 selected publications, describing the main impact and specifying your contributions to each particular study.

Deadline for applications: 20 November 2023, 23.59pm CET

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor. Once the assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.

You can read about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/

The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.

Interviews are expected to be held during December 2023.

The University of Copenhagen wish to reflect the diversity of society and encourage all qualified candidates to apply regardless of personal background.

Kilde: Jobnet.dk