PhD student

MSCA Doctoral Researcher for multi-modal AI to identify new immune targets
We have an open vacancy for a 3-year fully-funded PhD researcher position for developing multi-modal AI to define macrophage and immune targets for improved anticancer immunotherapy. The position is offered within the pan-European doctoral training network, Mac4Me (Macrophage Targets for Metastatic Treatment), which will train the next generation researchers in the emerging field of tumour cell-immune host interactions to identify new immunotherapy targets. The network is funded by the European Union’s Horizon Europe MSCA Doctoral Network programme. Mac4Me project will use animal-free organ-on-chip systems to recapitulate early liver, bone and brain metastasis during cancer development across the lifespan, such as neuroblastoma, breast and prostate cancer. The multi-modal data from these preclinical models will be integrated with real-world clinical data using AI approaches to identify new immune targets.

More information about theMac4Me project: https://www.van-weerden-lab.com/about

The Mac4Me Doctoral Network provides an innovative, multidisciplinary and cross-sectional approach, with a unique and dedicated research training programme to equip young researchers with scientific knowledge and transferable skills that are essential for today’s research and great demand in both academic and non-academic sectors. Mac4Me brings together multidisciplinary team of 18 partners across multiple countries in Europe (universities, research institutes and industry), and combines expertise in preclinical systems, systems biology, data sciences, AI research, and cancer research. The network will offer the successful candidates an unprecedented learning environment, including a common training program and research visits to both academic and industry partners. The PhD candidates will work in close collaboration with the other doctoral researchers through a diverse educational agenda of online and face-to-face meetings.

Oslo University Hospital is a workplace with great diversity. We believe that this is absolutely crucial to solving the tasks required of us. We therefore want this diversity to be reflected among the applicants for our positions and encourage everyone to apply regardless of who you are and what background you have.
  Key information

 Application deadline: 11.11.2024

 Employer: Oslo universitetssykehus HF

 Town/city: Oslo

 Title: PhD Candidate

 Positions: 1

 Full-time/part-time: Full-time

 Employment type: Contract

 Percentage of full-time: 100

 Webcruiter ID: 4874147616

 Start date: 01.12.2024

 End date: 30.11.2027

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The research group of Prof. Tero Aittokallio develops and uses computational approaches that combine multi-omics genomic and molecular profiling data and clinical information from cancer patients using mathematical and statistical approaches such as machine learning and network modelling; see https://www.ous-research.no/aittokallio/  The medical aim is to optimize treatment outcomes for individual patients using maximally predictive models and minimal biomarker signatures.

The group is now seeking a motivated PhD student, with strong skills in statistical data analysis and machine learning to work in the Mac4Me Doctoral Network. Objectives: 

1. Integrate spatial transcriptomics and single-cell RNA- sequencing data,
2. Identify tumour cell-macrophage interactions and their relation to clinical data,
3. Apply multi-modal AI algorithms to define new targets for improved immunotherapy.

The successful candidate will be employed at the Department of Cancer Genetics, located at the Institute for Cancer Research, and work in a multidisciplinary team. The PhD student will have the possibility to attend relevant courses at the University of Oslo, and present at national and international conferences. Each PhD has planned short-stay research visits to other partners of the Mac4Me Doctoral Network.

The PhD position will offer a vantage point in the rapidly developing field of immunotherapy targets, with versatile opportunities to learn and become an expert in the field, where there is a growing requirement for data scientists. Our multicultural and multidisciplinary organization prides itself in a working community that fosters creativity and diversity, and a relaxed workplace with a Nordic style of work-life balance.

Eligibility criteria
Please check carefully that you are eligible; all conditions below are compulsory and the EU mobility rule applies for all recruitments:
Transnational mobility:  At the time of recruitment, you must not have resided or carried out your main activity (work, studies, etc.) in the host country (Norway) for more than 12 months in the 3 years immediately prior to recruitment.
Early-Stage Researchers (ESRs): All researchers recruited in Mac4Me must have less than 4 years since the completion of their first MSc degree and have not been awarded any doctoral degree at the date of employment. 
English language requirements: All applicants must have good English skills and a certificate that proves those skills. Read more about the language and other admission requirements at the University of Oslo: https://www.med.uio.no/english/research/phd/regulations/supplementary-rules-pertaining-to-the-regulations.html#toc7 

Qualifications

• MSc degree in computer science, biostatistics, bioinformatics, biomathematics, or other relevant field
• Confident communication skills, interpersonal skills, and good scientific writing skills in English
• Experience in various bioinformatics data analysis tools for large-scale omics data analyses
• Good programming skills (e.g. Python, R) and ability to work with version control tools (e.g. Git)
• Previous knowledge of cancer research and preclinical model systems are considered an advantage

Personal qualities

• Willingness to learn multidisciplinary skills
• 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 single-cell and spatial datasets
• Competitive salary and yearly wage agreement
• Membership of pension fund and insurance