PhD Programme in Biomedical Data Science

Digitisation and advances in data science, including artificial intelligence (AI), which influence and change all areas of life, have a particular impact on life sciences and health-related sciences. For example, large data sets for each individual patient are already routinely collected and systematically recorded. A further increase in complexity is expected in the coming years due to increasing use of molecular and imaging diagnostics. The degree of resolution – already at single-cell level – will continue to increase in all disciplines of life sciences, and the need to process and combine huge data sets such as the phenome, genome and exposome, including continuously measured health data such as heartbeat or activity measurements of wearables, will increase. The processing and analysis of such complex data is one of the greatest challenges for life sciences, and in particular, for health-related sciences. However, there are few experts, and application is limited and constrained by the scientific environment, which hinders the full use of existing and expected data. As part of the Translationsallianz in Niedersachsen (TRAIN), which integrates various regional partners from translational research, the concept of a cross-university PhD programme involving non-university institutions was developed to enable the combination of different scientific and technological disciplines relevant to biomedical data science. The start of "BIOMEdical DAta Science (BIOMEDAS)" took place in the winter semester 2020 at Hannover Medical School (MHH), which is the leading institution of the new programme of the Hannover Biomedical Research School (HBRS). BIOMEDAS is directed to students who are interested in combining disciplinary knowledge with the skills of a data scientist and working at the interface of bioinformatics, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners are further developed in different areas, which open up numerous opportunities for interdisciplinary exchange. In particular, projects in the areas of “exploiting the potential of available biomedical and clinical data sources“, “making use of biomedical data to realise personalised medicine”, “understanding pathomechanisms through biomathematical modelling” and “employing artificial intelligence to develop tailored diagnostic and treatment strategies” will be researched by BIOMEDAS students. The PhD programme applies a collaborative training principle involving supervisors from the individual partners. Annual meetings with the thesis advisory committee and a combination of a core research project and individual courses form the basis of the training programme.