Postdoctoral Researcher in Computational Genomics and Machine Learning through the NORPOD program
4 days ago
NORPOD is a collaborative postdoctoral program of the Nordic EMBL Partnership for Molecular Medicine. The partnership is a network of four national research centers across the Nordics and the European Molecular Biology Laboratory (EMBL), with complementary research expertise at the forefront of molecular medicine research. With the NORPOD program, the Nordic EMBL Partnership aims to foster the next generation of researchers in molecular medicine by implementing joint postdoctoral research projects to nurture strong competences and research excellence.
FIMM is currently seeking a Postdoctoral Researcher to join the Machine Learning in Biomedicine group, in collaboration with the Precision Cancer Epigenomics group at NCMM, through the NORPOD program.
Summary of the project
Human tumors are characterized by recurrent mutations in the well-defined cancer driver genes, but also non-mutational epigenetic reprogramming and phenotypic plasticity controlled by transcription factors (TF) are important contributors to tumorigenesis. Extensive consortium efforts have mapped the mutational and epigenetic landscapes of human cancers. However, the commonly used epigenomics methods such as ChIP-seq are correlative in nature and report a lot of spurious sites that might not be linked to gene expression, highlighting the need for novel innovative approaches to understand cancer genome and epigenome. Here, we will utilize cutting-edge long-read nanopore sequencing combined with deep machine learning approaches to model the epigenetic changes and mutational mechanisms in cancers originating from endodermal tissues. The goal is to reveal novel mechanistic details about the development of human cancer.
Tasks
The postdoctoral researcher will analyze NaNOME-seq, ATAC-seq and RNA-seq data to model the gene regulatory logic in epithelial cells. In addition, the researcher will investigate the effects of DNA adducts on methylome, transcriptome, and the gene regulatory logic.
Skills, expertise and/or qualifications
We expect a successful candidate to have a PhD degree from a relevant field with skills and experience in computational genomics and machine learning. Familiarity with the above-mentioned data types is an asset, as well as a strong publication record in a relevant field. Good written and oral communication skills in English are expected.
Implementation
The NORPOD Fellow will be employed at the Machine Learning in Biomedicine group (FIMM, University of Helsinki, Finland). To promote collaboration between the two groups, this position will involve short or long-term stays at and communication with the Precision Cancer Epigenomics lab (NCMM, University of Oslo, Norway). Successful candidates are expected to travel between the labs to conduct work required for the research project, foster synergies and advance our goals. Expenses related to the research visits will be covered.
Contract & salary
The job is for a fixed term of 2.5 years. A trial period of 6 months will be applied. Salary will depend upon the applicant's level of skills, knowledge, and abilities and is based on the university salary system. The starting salary will be ca. 3,500 – 3,800 euros/month, depending on the appointee's qualifications and experience and including a salary component based on personal performance. Standard Finnish pension benefits and occupational health care are provided for University employees. We welcome applicants from a variety of gender identities, linguistic and cultural backgrounds.
Selection process
The collaborating PIs of the research project will shortlist and video interview the top candidates. Top candidates will be invited for an online interview, conducted by an independent selection panel where they will also be given the opportunity to pitch the project plan. NORPOD Fellowships will be awarded based on the recommendation of the selection panel.
How to apply:
The application should include (i) CV with a complete list of scientific publications, (ii) a one-page statement of motivation for applying for this position, (iii) contact information of at least two reference persons who have agreed to provide a written statement on behalf of the applicant. To apply, please submit the application through the University of Helsinki electronic recruitment system by clicking on Apply for job. Internal applicants (i.e., current employees of the University of Helsinki) please submit your applications through SAP Fiori https://msap.sap.helsinki.fi. Please apply no later than 24th of January 2025.
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