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Automated Device for the Detection of intra- and extra-cellular Parasites
Current parasite diagnosis in particle suspension mostly relies on conventional manual microscopic analysis. It requires highly trained personnel, is restricted to expert laboratories, it is time-consuming and limited regarding statistics. Flow Morphometry, on the other hand, enables automated high-resolution morphological analysis of quickly moving suspended objects with high statistical power, at best in real time. With tailored algorithms and machine learning, this method is applicable to prokaryotic and eukaryotic cells, and environmental samples [e.g., 1]. In this project, Flow Morphometry will be applied to complex biological samples of high medical significance [e.g., 2].
The PhD project focusses on artificial intelligence guided parasite analysis in tropical medicine. Custom-made, automated diagnostic devices will be developed and used for the analysis of parasites in blood and faeces. The project comprises conception and construction of electronic-, liquid handling- and optical- equipment as well as implementation of execution and control software. Furthermore, it covers artificial intelligence and method validation with extended biological sample sets.
- Sierra F DA, Melzak KA, Janetzko K, Klüter H, Suhr H, Bieback K, Wiedemann P. Flow morphometry to assess the red blood cell storage lesion. Cytometry A. 2017 Sep;91(9):874-882. doi: 10.1002/cyto.a.23127. Epub 2017 May 4. PMID: 28472540.
- Cyrklaff M, Sanchez CP, Hanebutte L, Jäger J, Schwarz US, Lanzer M. An Improved Method for Assessing Antigen Presentation on the Surface of Plasmodium falciparum-Infected Erythrocytes by Immuno-Electron Microscopy. Methods Mol Biol. 2022;2470:445-455. doi: 10.1007/978-1-0716-2189-9_33
Diagnostic hardware & device layout and development, software development, artificial intelligence, flow morphometric microscopy / flow morphometry, liquid handling, biological sample handling and method validation, parasitology
This project is a cooperation between the University of Heidelberg (Prof. Dr. M. Lanzer, Dr. P. Hoepffner, Center of Infectious Diseases, Parasitology, Universitätsklinikum Heidelberg) and the Mannheim University of Applied Sciences (Prof. Dr. P. Wiedemann, Prof. Dr. H. Suhr, Faculties of Information Technology and Biotechnology).
Candidates should have a Master’s degree in information technology, mechatronics, engineering or related fields. Technical and hardware skills, software knowledge and interest in interdisciplinary work are mandatory, experience in artificial intelligence and biotechnology are an asset. Also, we encourage candidates with a migratory background to apply.