Data science engineer (Postdoc)

Applications are invited for a talented and motivated data science engineer to join a collaborative project between the Trinity Kidney Centre, the School of Computer Science and Statistics and the ADAPT Research Centre at Trinity College Dublin, and the German Research Centre for Artificial Intelligence (DFKI), helping to bridge the gap between artificial intelligence and cutting-edge medical research.

You will be responsible for developing and maintaining data science pipelines that enable reproducible and effective statistical modelling of rare diseases from sensitive electronic health record data, and in writing and extending statistical software to implement modern machine learning methods. The work will focus on modelling and maximising data quality and alignment with relevant data standards. The successful candidate will work at Trinity College while being jointly supervised by researchers from DFKI.


  • The post holder will be a data scientist required to undertake research on projects developing algorithms linking multi-modal assessments of immune system activation and clinical status.
  • Implement machine learning algorithms and data processing pipelines as reusable, modular software packages following best programming practices.
  • Disseminate research findings with the preparation and publication of results in leading international journals.
  • Attend and present research internally and at national and international conferences.
  • Participate and assist/train colleagues in related research projects
  • Prepare reports and professionally engage with academic and industrial partners.
  • Leadership within the PARADISE consortium and DFKI, including helping to run symposia, group meetings and guidance of junior team members.


  • PhD in data science, computer science, biostatistics, computational biology, machine learning or a similar field.
  • Appreciation for challenges of longitudinal analysis of sparse, real-world patient data
  • A solid understanding of data science pipelines, version control, software and data testing and best practices
  • An interest in reproducibility, transparency, data ethics, algorithmic fairness and other aspects of responsible data science
  • Awareness of concepts such as personalized medicine, hybrid machine learning or data augmentation
  • Ability to balance technical requirements with making complex concepts understandable to stakeholders and collaborators
  • The ability to work independently on a project, as well as co-operatively within a team, is essential.

Technical skills

  • Proficient in R (essential) and at least one of the Python or Julia programming languages (desirable), with experience in package development
  • Must be a well-organized data scientist with: - excellent writing, communication and interpersonal skills - non-native English speakers require at least IELTS 6.5 (with at least 6 in all components) or equivalent.


Deadline: 7 July 2023

For more information and to apply for this role, please see the full posting on the ADAPT Centre web site.

As this role is officially based at Trinity, please apply through their web site, not through the usual form here on the DSA/Vollmer Group web site.

David Antony Selby
David Antony Selby
Senior Researcher

My research interests include latent variable modelling, reproducibility, citation networks and applications of statistics and machine learning to healthcare.