With its main focus on methods of artificial intelligence (AI) and tools that model, predict and explain the development of diseases over the life course, Lifespan AI will use high-dimensional, life-spanning data that will be assembled from longitudinal epidemiological studies and supplemented with biological, social, and lifestyle information. Here, AI research goes hand in hand with biostatistics, epidemiology and the integration of AI in health research.
Lifespan AI covers six projects grouped into three themes: Data and Methods (D), Models and Interpretation (M), and Inference and Causality (C) at the intersection of computer science, epidemiology and statistics. The six PhD projects concern: (i) D1 – Deep Integration of Health Data, (ii) D2 – Lifespan Predictions, (iii) M1 – Normalizing Flows for Lifespan Health Data, (iv) M2 – Lifespan Knowledge Representation, (v) C1 – Explainable AI across the Lifespan, and (vi) C2 – Causal Discovery across the Lifespan. Further three PhD intersection topics connect the themes, i.e. (vii) D1/M2 – hybrid universal embeddings, (viii) M1/C1 – model interpretation, and (ix) D2/C2 – design & harmonization. These projects are supported by a (x) discipline connector and a (xi) data steward.
At University of Bremen and Leibniz Institute for Prevention Research and Epidemiology –  BIPS up to 9 doctoral positions (salary scale TV-L E13 100%) for the areas (i) to (ix) and 2 research positions (salary scale TV-L E13 50%) for the areas (x) and (xi) are available for scientific qualification according to § 2 para. 1 WissZeitVG, limited to 36 months.
With cutting-edge laboratories and data infrastructure at BIPS, CSL Biosignals Lab, ZeTeM, and KKSB, Lifespan AI offers access to excellent facilities, data and computing infrastructure, attractive workplaces, diverse and responsible tasks, and a wide scope of advanced training options, and flexible working time models.
All scholars are supervised by an interdisciplinary team of at least two highly qualified principal investigators providing their complementary expertise, infrastructure, and networks. Scholars are encouraged to grow their skills and networks by visiting partner and other world-renowned institutions for extended research stays.
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Successful candidates should have completed their master studies (or complete them very soon) in computer science, (bio-)mathematics, (bio-)statistics, data science or related fields. Opportunities for qualification scholarships for candidates with other related backgrounds and/or study degrees are also available.
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We aim to balance the diversity (f/m/d) of employees. We kindly encourage female applicants to apply for this job. Recognized severely disabled persons will be preferred if they are equally qualified.
Further information about the team, projects, and recruiting process of Lifespan AI can be found at lifespanAI.de.
Please follow the instructions on this website on how to submit your application (including your professional CV, certificates, and research interests) until March 31st, 2023.
A virtual assessment event will take place in April 2023.
Applications for these positions have now closed (deadline March 31st, 2023). We thank everyone who applied.