Department of Psychiatry and Psychotherapy of the University Medicine Greifswald
We are a young, interdisciplinary research team with expertise in bioinformatics, biology, statistics, and psychiatry and we are looking for interested master students from the fields of bioinformatics/applied mathematics/ biomathematics/statistics or similar. We are interested in the statistical modeling of complex biomedical relationships between omics data (e.g. Metabolomics) and psychiatric or kidney diseases.
We plan to analyze a large number of publicly available Metabolomics data sets by network analysis in close collaboration with the University and Research Wageningen, NL. We are looking for an enthusiastic master student, who is interested in the analysis of complex data sets by alternative statistical/machine learning methods.
We have both metabolomics and polysomnographical data collected from the SHIP-TREND study. We plan to conduct a thorough statistical analysis of possible associations between metabolites and single polysomnographical parameters. We are looking for an enthusiastic master student, who is interested in the analysis of complex data sets by alternative statistical methods.
The goal of this master thesis is the cost-optimized generation of novel multivariable biomarker signatures for the prediction of renal failure. We have access to a large cohort with more than 5,000 chronic kidney disease patients, who have been followed up for four years. We are looking for an enthusiastic master student, who is interested in the analysis of complex data sets by machine learning methods and in the development of novel machine learning algorithms.
We plan to generate novel multivariable biomarker signatures, e.g., to predict renal failure, for specific renal diseases, e.g., IgA nephropathy or diabetic nephropathy. We have access to a large cohort with more than 5,000 chronic kidney disease patients, who have been followed up for four years. We are looking for an enthusiastic master student, who is interested in the analysis of complex data sets by machine learning/statistical methods.
We are looking for master students who have fun with the analysis of complex biological/clinical data. Basic knowledge of statistical software (R) is required.
Prof. Dr. Helena Zacharias
Klinische Datenwissenschaften
Peter L. Reichertz Institut für Medizinische Informatik
der TU Braunschweig
und der Medizinischen Hochschule Hannover
Standort Hannover
Et-Cetera-Gebäude, Karl-Wiechert-Allee 3
Postanschrift: Medizinische Hochschule Hannover, PLRI – OE 8420,
Carl-Neuberg-Straße 1
30625 Hannove
Germany
helena.zacharias@uni-greifswald.de
CKDNapp is sponsored by the German Federal Ministry of Education and Research (BMBF)
within the framework of the e:Med research and funding concept (grants no. 01ZX1912A, 01ZX1912B, 01ZX1912C, and 01ZX1912D).
