Data Scientist for the Center for Health Data Science

Copenhagen University
November 20, 2023
Offerd Salary:Negotiation
Working address:N/A
Contract Type:Other
Working Time:Negotigation
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The Center for Health Data Science (HeaDS), Faculty of Health and Medical Science, University of Copenhagen is hiring a data scientist to join our project building a national "sandbox" infrastructure in health data science. The position is for two years with potential for extension and the start date is the 15th of January, 2024 or as soon as possible.

The National Health Data Science Sandbox for Training and Research The Health Data Science Sandbox is a national project coordinated by the Center for Health Data Science (lead PI: Prof. Anders Krogh) at the University of Copenhagen. We're working with a network of health data science experts to build resources for training and research on academic supercomputers in Denmark. We are establishing a national infrastructure, a “sandbox”, in which students and researchers can work with realistic health data that is non-person-sensitive (i.e. data is either anonymized or synthetic) in academic supercomputing environments. Our Sandbox team is building training modules that pair topical datasets with recommended analysis tools, pipelines, and learning materials/tutorials in a portable, containerized format. The Sandbox project started in 2021 and is now deploying modules in genomics, transcriptomics, proteomics, and modeling of health records (check out our website for more details). Funded by the Novo Nordisk Foundation, our co-PIs and collaborating staff can be found at Aalborg University, Aarhus University, Technical University of Denmark, and University of Southern Denmark.

About Center for Health Data Science:

The aim of the Center for Health Data Science (HeaDS), launched in March 2020, is to strengthen data science research and use at the Faculty of Health and Medical Sciences. The Center functions as a hub for research groups throughout the Faculty to establish data science as a topic of research in its own right. The SUND DataLab within the Center provides data science support for all research groups at SUND and runs courses to improve the data science skills of the biomedical researchers. The long-term goal of the Center is to house multiple research working within the field of health data science. Our philosophy is a relaxed work environment driven by inspired and independent people.

The job of Sandbox Data Scientist :

The main tasks of a Sandbox Data Scientist are to develop training materials for students and researchers and deploy these materials on HPC infrastructure alongside online tutorials and in-person workshops for students and staff at Danish universities. You will get to utilize your expertise and specific competencies in combination with that of your colleagues to best cover the interests of the Danish health data science research community and broadly increase data science fluency. We are looking for someone excited to also learn new data science skills via our collaborations with other educators and on request by Sandbox users. We want to highlight new approaches and tools (especially those with Danish developers!) and also have a special interest in generation of safe-to-share health datasets (a major opportunity for creative problem solving).

The Sandbox team of 6 data scientists works together fluidly through weekly online meetings and monthly updates for all project partners. We also aim for bi-annual in-person meetups, with growing connections to a national network of health data science researchers and educators. As a UCPH Sandbox Data scientist, you are also expected to represent HeaDS, coordinate training efforts with the SUND DataLab, and participate in outreach at the SUND Faculty and beyond.

Your profile:

  • MS or PhD degree in bioinformatics, computer science, biostatistics, or a field of science relating to data science
  • Strong programming skills in R and/or Python, including R Markdown and/or Jupyter Notebooks
  • Familiarity with Linux
  • Experience with code sharing and collaboration using git/github
  • Experience with cloud computing and HPCs, particularly Computerome or UCloud
  • Experience with one of the following research areas:
  • RNAseq data (mapping, quantification, down-stream analysis)
  • Single cell analysis (RNA, DNA)
  • Quantitative mass spectrometry data (proteomics, lipidomics, metabolomics)
  • Biostatistical analysis of large biomedical/health record datasets
  • Analysis of biomedical images
  • Machine learning approaches within the field of medical research
  • An ideal candidate would meet some of the following criteria :

  • Well-versed in working with large datasets, e.g., storage, data management, and computing
  • Experience with multi-omics integration approaches
  • Experience with sensitive medical data and GDPR compliance rules
  • Experience with deep learning approaches to health record analysis or generation of synthetic health data
  • Valued personal competencies :

  • Independent, creative, forward-thinking, and have good decision-making skills
  • Outgoing and good with people, and you enjoy teaching within your field of expertise
  • Proficient in English
  • Flexible and innovative – our project is unorthodox in the academic setting and we hope to attract thoughtful people with a vision for what health data science training is needed and can become!
  • For further information regarding the position, please contact Sandbox project manager Jennifer Bartell: [email protected].

    Terms of Employment:

    The employment will be as academic research staff in accordance with the provisions of the collective agreement between the Danish Government and AC (the Danish Confederation of Professional Associations). Your salary level will be based on seniority, and a supplement may be negotiated. There is a monthly contribution to a pension fund (17.1% of the salary).

    How to apply: Your online application must be submitted in English by clicking ‘Apply now' below. The application must include:

  • A short letter of motivation
  • Curriculum vitae including publications
  • Masters and PhD diploma (or equivalent).
  • References and/or letters of recommendation.
  • Application deadline: Sunday the 12th of November, 2023 at 23:59 CEST.

    Please note that only applications submitted online by the deadline and consisting of the above listed documents will be considered. Applications will be reviewed on a running basis, and those received after the deadline will not be taken into consideration.

    Interviews will be taking place end of November.

    University of Copenhagen wish to reflect the diversity of society and welcome applications from all qualified candidates regardless of age, disability, gender, nationality, race, religion or sexual orientation. Appointment will be based on merit alone.

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