Applied Machine Learning Researcher

4 days ago


Copenhagen, Copenhagen, Denmark PARETO SECURITIES AS Full time
Our Project

PARETO SECURITIES AS is involved in a pioneering project to leverage large-scale multimodal biomedical data combined with focused innovation in statistical and computational methods, including machine learning, to advance our understanding, treatment, and prevention of human disease. This project focuses on prediction, course, and outcome in psychiatry leveraging the large-scale genetic cohort (iPSYCH) in addition to nationwide registers with electronic health data. The project aims to develop integrative psychiatric risk models that leverage multi-modal information, evaluate prediction models, and estimate absolute population risks in the population at large. The project will explore risk and prediction for adverse outcomes in relatives to mental health patients, at prediction and courses of psychiatric diseases for implementation in everyday work in a clinical context, and estimated prognosis to explore on preventive clinical approaches and treatment options, estimate absolute disease risk, prognostic accuracies, and risk of comorbidities. All previous attempts towards more precision psychiatry have not been suited for implementation in clinical practice so far. Therefore, the field of psychiatry still has many unknowns, remaining as a challenge to which, we believe this project will greatly contribute. This will pave the way to actual clinical implementation that would enable the advancement of precision psychiatry to the next level. When successful, the developed models will be tested clinically in our clinical test center for data-driven treatments as part of the EpiPsych project.

About the Position

The offered position is a 1-year position to start with the possibility to prolong it to a 3-year PhD or Postdoc position in total at the Copenhagen Research Centre for Biological and Precision Psychiatry. The candidate will combine a strong level of technical knowledge within AI, data management, and data analysis, as well as scientific interest in the clinical implementation. The candidate will focus on applied research with primarily application of existing statistical, AI/machine, and deep learning methods to large-scale data sources.

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