PhD Student in AI for Molecular Diagnostics (w/m/d)
- Anstellung: Teilzeit
- Verfügbarkeit: ab 01.08.2023
- Befristung: bis 31.07.2026
- Führungsverantwortung: Nein
ScaDS.AI (Center for Scalable Data Analytics and Artificial Intelligence) Dresden/Leipzig is a center for Data Science, Artificial Intelligence and Big Data with locations in Dresden and Leipzig. It is one of five new AI centers in Germany funded under the federal government’s AI strategy and is established as a permanent research facility. In collaboration with the Fraunhofer IZI and the Institute of Clinical Immunology of Leipzig University, we offer a position as PhD student (m/f/x) – AI for Molecular Diagnostics (65%)
We are searching for an outstanding and highly motivated PhD student interested to transfer machine learning applications in biomedicine into the clinic. Many cancers still cannot be cured with standard treatments, so new therapeutic strategies are needed. The adoptive cellular immunotherapy with chimeric antigen receptor (CAR) immune cells, which involves modifying a patient’s immune cells ex vivo with CARs that can recognize target antigens on tumour cells, is a promising approach. You will take advantage of machine learning methods for single-cell multi-omics in order to decipher disease pathogenesis in relation to treatment response and side effects of cellular immunotherapies. This includes data science and algorithm development, bioinformatics for single cell and spatial transcriptomics as well as development of software prototypes as medical device for applications in personalised medicine.
We offer work within a cutting-edge scientific project in an interdisciplinary team and in close collaboration with our clinical partners. You will utilize and develop machine learning algorithms to solve problems in molecular diagnostics.
- A Master degree in bioinformatics, computer science, mathematics, biology, chemistry or physics.
- First experiences with the processing and statistical analysis of omic-wide datasets (on single cell resolution is a plus).
- Experiences in at least one of the programming languages Python, Java, C, or C++.
- Sound background in machine learning, statistical learning and neural networks.
- Sound background in the R statistical framework as well as Unix/Linux operating systems and Git.
- A core understanding of genetics, molecular biology and computational biology.
- Excellent communication and inter-personal skills and be capable of working with an interdisciplinary team.
- Excellent written and verbal skills in English.
Your application should contain:
- cover letter
- detailed CV
- references (optional)
Please send your complete application with the required documents to firstname.lastname@example.org
or by uploading a PDF file via the job portal linked below. Don't hesitate to contact Dr. Kristin Reiche upfront for any questions or further information.
Dr. Kristin Reiche
Tel. 0341 35536 5223