Postdoctoral researcher / Cancer Data Science & Deep Learning

Postdoctoral researcher / Cancer Data Science & Deep Learning

 

 

Background

 

A 2.5-year postdoctoral position with flexible starting date is available in the Cancer Data Science group led by Mariike Kuijjer at iCAN Flagship in Digital Precision Cancer Medicine at the Faculty of Medicine, University of Helsinki. The project will focus on using and extending deep learning-based approaches developed within the group to integrate bulk multi-omics cancer data. 

 

The Kuijjer group, established in 2018 at the University of Oslo, has recently expanded to the University of Helsinki. The group specializes in developing computational methods to understand the regulatory mechanisms driving cancer heterogeneity and progression by integrating genomic data into genome-wide regulatory networks. Current projects include (i) modeling distal regulatory interactions, (ii) modeling networks based on single-cell and spatial omics data, and (iii) integrating regulatory profiles with multi-modal data. These efforts aim to uncover regulatory mechanisms behind cancer and to develop predictive models of cancer outcomes and treatment resistance. For more information, visit kuijjerlab.org.

 

The advertised project focuses on extending a deep learning framework, originally developed by the Kuijjer group for integrating single-cell multi-modal data, to bulk multi-omics cancer datasets. This framework incorporates biological data dependencies within a hierarchical Variational Autoencoder, enabling the modeling of both shared and data type-specific variability. By doing so, it provides insights into the regulatory mechanisms underlying cancer. The research will leverage a large in-house dataset from iCAN, complemented by publicly available data, to examine transcriptomic dependencies on transcription factor abundance and somatic mutations. These efforts aim to enable pan-cancer subtyping and uncover regulatory processes contributing to cancer.

 

The candidate

 

We seek a motivated candidate with a strong interest in computational cancer research, who is enthusiastic about applying deep learning methods to cancer data. We require the candidate to have documented experience in either large-scale genomics data analysis with computational or approaches/biostatistics, or machine learning/deep learning. Experience with both of these is a strong advantage. Experience with the application of ML/DL approaches to omics data, computational tool development, multi-omics data integration, and knowledge of cancer biology and/or gene regulation are also considered a strong advantage,  but not strictly required. The applicant should be collaborative, creative, and capable of working both independently and as part of a team within a multidisciplinary research environment spanning two Nordic countries, with active groups in Helsinki and Oslo.

 

The position is open to applicants with a PhD degree in computational biology, bioinformatics, computer science, biostatistics, cancer genomics, or related fields. Candidates who are completing their PhD thesis are welcome to apply and should mention the expected date of their defense and any remaining steps to completion in their cover letter, and include a letter with this information by their current supervisor to the application.

 

The appointment is a fulltime position and is made for a period of two and a half years with possible extension depending on future funding.

 

 

Qualification requirements

 

•    PhD degree in computational biology, bioinformatics, computer science, biostatistics, cancer genomics, or a related field. Applicants with a background in biology or (bio)medicine are welcome to apply, provided they have documented expertise in deep learning
•    Proficiency in programming (such as Python, R, Bash)
•    Documented research experience in at least one of these: large-scale omics data analysis, machine learning and/or deep learning. Candidates with coursework or other relevant training in the second area are encouraged to highlight this in their application.
•    Experience with high performance computing and GPU acceleration tools (e.g. CUDA) and deep learning frameworks, such as TensorFlow or PyTorch is a strong advantage
•    Experience with VAEs or related frameworks and statistical analysis of high-throughput omics data is an advantage
•    Knowledge of multi-modal data integration, gene regulation, cancer, and/or network biology is considered a plus
•    Strong analytical and problem-solving skills with the ability to develop and maintain computational tools for biological data analysis
•    Teamwork skills and the willingness to collaborate, share ideas, and contribute to a multidisciplinary research environment that spans two Nordic countries, with active groups in both Helsinki and Oslo
•    Strong communication skills in English, with both written and verbal proficiency

 

 

We offer

 

•    We offer a salary of 3 534,00 – 4 338,29 €/month depending on the candidate's qualifications
•    A professional, stimulating working environment
•    The University of Helsinki also offers comprehensive services to its employees, including occupational health care and health insurance, unemployment and pension fund, a generous holiday package, sports facilities, and opportunities for professional development: https://www.helsinki.fi/en/about-us/careers.

 

 

How to apply

 

The application, including attachments, must be delivered through the electronic recruiting system. The application must include:
(1) A cover letter, stating your motivation, scientific background, and research interests. Please highlight the specifics of how you match the required expertise in the cover letter
(2) A detailed CV with a list of publications
(3) 2-3 references (name, institution, e-mail, telephone number, and relation to the candidate)

These should be uploaded in .pdf format. Please submit your application through the web-based recruitment system linked in the announcement. While the recruitment system includes a basic CV, we ask candidates to also include a separate, detailed CV in .pdf format with their application. Applications without a cover letter and/or detailed CV will be rejected. The closing date for applications is 31.5.2025.

 

The University of Helsinki welcomes applicants of any gender and age, linguis-tic or cultural background, or minority group.

Click this link to read about accessibility and inclusivity at our University.

 

Contact information

 

Inquiries about the position can be directed to Mariike Kuijjer.

 

 

 

About us

The Faculty of Medicine promotes high quality scientific research. It provides research-based undergraduate and postgraduate education in medicine, dentistry, psychology and logopedics, and an international Master's Programme in Translational Medicine. It also offers psychotherapist education. In addition to its teaching and research activities, the faculty serves as a significant expert organisation in the healthcare sector and contributes to the discourse on ethics in the field. The faculty aims to be one of the best medical research faculties in the world, while reinforcing its status as a distinguished institution of multidisciplinary education in healthcare.
The Faculty of Medicine at the University of Helsinki constitutes the academic medical centre together with HUS Helsinki University Hospital and the Helsinki Institute of Life Science (HiLIFE). This medical centre has been successful in international comparisons, ranking among the top 10 medical campuses in Europe and the top 50 globally.

 

JOIN US TO BUILD A BETTER WORLD – TOGETHER!  

 

 #HelsinkiUniCareers