Postdoctoral Fellowship in Metrology for Artificial Intelligence in Medicine
To reinforce our interdisciplinary team working on Metrology for Artificial Intelligence for Medicine (M4AIM), we are looking for a
to work on metrological and quality aspects of machine learning (ML) and artificial intelligence (AI) systems in medicine. The position is offered for three years.
Shortlisted candidates will be invited to online interviews taking place between 10th and 14th January 2022.
Interested candidates are expected to outline a possible project in a short research statement.
Topics of interest include
Novel ML/AI methods or inverse solutions that deal with spatio-temporal physiological time series
Novel criteria to quantify quality aspects of ML/AI systems in medical applications, such as robustness, uncertainty calibration, explainability, privacy or fairness
Novel ML/AI methods to improve above-mentioned quality aspects
Novel ML/AI techniques that utilize physics knowledge about the data-generating process or techniques that approximate or accelerate physics-based simulations
Collection and annotation of reference data for specific use cases
Generation of realistic synthetic data for specific use cases
Development of benchmarking protocols for specific use cases
Development of infrastructure to store and curate reference data, and to conduct standardized benchmarks
Development of guidelines, standards, or protocols that could feed into regulatory frameworks for ML/AI in medicine
Possible clinical use cases include
Magneto- and electroencephalography
Magnetic resonance imaging
Clinical routine data (e.g. from intensive care, peri-operative care)
Electronic health record data
The Postdoctoral project will be hosted at the Berlin campus of PTB in Department 8.4 "Mathematical Modelling and Data Analysis". The department is tightly interconnected with numerous internal and external partners, including
Department 9.4 "Metrology for Digital Transformation"
The Computer Science Department at Technische Universität Berlin
Charité - Universitätsmedizin Berlin (Berlin's medical school)
The Focus Group AI for Health of ITU and WHO
The Fraunhofer Heinrich Hertz Institute (HHI)
Other member institutes of the German Quality Infrastructure such as DIN and BAM
A PhD in a technical discipline (e.g., computer science/mathematics/statistics/physics) or in medicine
Strong and up-to-date expertise in the theory and practice of ML/AI and statistics
Strong expertise at the intersection of ML/AI and Medicine, backed by a solid track record
Ability and interest to adopt both a scientific and a regulatory perspective
Enthusiasm, collaborative spirit, and willingness to drive efforts to define and advance the quality control of ML/AI systems in medicine
Are you interested? Then we are looking forward to receiving your application.
Please fill our online application form and upload as attachements your letter of motivation, a complete CV, a research statement (1-2 pages), degree certificates and transcripts.
For degrees obtained outside the EU please check at https://anabin.kmk.org/anabin.html whether they are acknowledged in Germany.