Research Associate (m/f/d), E13

at  Carl von Ossietzky Universitt Oldenburg

Faculty VI Medicine and Health Sciences encompasses the areas of human medicine, medical physics and acoustics, neuroscience, psychology, and health services research. Together with the four regional hospitals, Faculty VI forms the University Medicine Oldenburg. Furthermore, there is close collaboration with the University Medical Center of the University of Groningen.
The division “AI4Health” (headed by Prof. Dr. Nils Strodthoff) in the Department of Health Services Research of Faculty VI - Medicine and Health Sciences at Carl von Ossietzky University Oldenburg are seeking to fill a position at the earliest possible date for a

Requirements

• Completed university degree in Computer Science, Mathematics, Physics, or related fields
• Excellent command of English, both written and spoken
• Theoretical and practical knowledge (the former demonstrated through relevant courses/completed online courses, the latter demonstrated through personal projects) in the field of machine learning, especially in the area of deep neural networks
• Very good programming skills in Python and in the Machine Learning framework PyTorch
• High degree of independence, flexibility, and teamwork skills as well as willingness to work in an interdisciplinary manne

The advertised position aims to develop data-driven prediction algorithms in the context of various diagnostic disciplines. In a first step, prediction models for single modalities are to be developed for selected use cases. In a second step, different modalities are to be combined to demonstrate the feasibility of multimodal predictions. The focus of the advertised position is on data from laboratory medicine, immunology, and microbiology. The project has a strong interdisciplinary character and requires, in addition to prior knowledge in the field of machine learning, an enjoyment of interdisciplinary collaboration with experts from different diagnostic application areas, learning about different data modalities, and selecting and adapting suitable learning algorithms. Research results of both methodological and applied nature should be published in professional journals and presented at relevant conferences.
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Requirements

• Completed university degree in Computer Science, Mathematics, Physics, or related fields
• Excellent command of English, both written and spoken
• Theoretical and practical knowledge (the former demonstrated through relevant courses/completed online courses, the latter demonstrated through personal projects) in the field of machine learning, especially in the area of deep neural networks
• Very good programming skills in Python and in the Machine Learning framework PyTorch
• High degree of independence, flexibility, and teamwork skills as well as willingness to work in an interdisciplinary manner

Desirable

• Experience in medical-diagnostic application fields, especially bioinformatics, demonstrated through completed courses or personal projects
• Proven experience in interdisciplinary communication
• Experience with scientific presentations and publications
• Knowledge of German