PhD student

Work tasks

The research group of Prof. Tero Aittokallio focuses on developing and applying integrated computational-experimental approaches to better understand the mechanisms behind cancer progression that enable accurate predictions of system-level phenotypic responses to genetic and chemical perturbations. The group is now seeking a motivated PhD student, with strong computational and analytical skills, and an interest in applying AI and machine learning approaches for analysing and integrating multi-omics data from genomics, radiomics and pathomics for personalized treatment predictions. The PhD student will be working in a multi-disciplinary environment, where the common objective is to find individualized treatment options for cancer patients based on multi-omics biomarker panels.  

The successful candidate will be employed at the Department of Cancer Genetics, located at the Institute for Cancer Research at the Norwegian Radium Hospital, and work interdisciplinary alongside with molecular biologists, medical doctors, statisticians and engineers. The PhD student will also work with researchers from Oslo Centre for Biostatistics and Epidemiology (OCBE), a joint centre between University of Oslo and Oslo University Hospital.  The PhD student will have the possibility to attend relevant courses, both at University of Oslo and Oslo University Hospital, and present at international conferences. We are seeking a highly motivated candidate for collaborative projects that require skills for developing and applying machine learning methods and writing manuscripts

Qualifications

• Master degree in computer science, information technology, system engineering, biostatistics, bioinformatics, biomathematics, or other relevant field
• Fluent in English and good scientific writing skills
• Past experience in AI and machine learning
• Good computational and programming skills (R, Python, SQL)
• Previous experience in cancer research is an advantage

Personal qualities

• High work capacity and productivity
• Able to work independently and in teams
• Motivated and solution oriented 
• Multidisciplinary communication skills
• Commitment to meeting deadlines

We offer

• An inspirational and dynamic work environment 
• Flexible working hours and regular supervision 
• Access to unique and high-quality datasets 
• Competitive salary and yearly wage agreement                                                                                                                                                                                                          
• Membership of pension fund and Insurance