Universität Stuttgart
70569 Stuttgart - Deutschland
Biologe/Biologin
Arbeit
Vollzeit
ab 10.02.2026
Beschreibung
We are seeking a highly motivated PhD candidate to join our Systems Biology Department at the Institute of Biomedical Genetics (IBMG), University of Stuttgart (https://www.ibmg.uni-stuttgart.de/de/systems_biology/). The successful applicant will study TGFbeta-induced cellular decision making in health and disease using a combination of kinetic modeling, bioinformatic data analysis and/or AI. The appointment will initially be limited to 3 years.
The University of Stuttgart is one of the leading ... weiter lesen
The University of Stuttgart is one of the leading ... weiter lesen
We are seeking a highly motivated PhD candidate to join our Systems Biology Department at the Institute of Biomedical Genetics (IBMG), University of Stuttgart (https://www.ibmg.uni-stuttgart.de/de/systems_biology/). The successful applicant will study TGFbeta-induced cellular decision making in health and disease using a combination of kinetic modeling, bioinformatic data analysis and/or AI. The appointment will initially be limited to 3 years.
The University of Stuttgart is one of the leading technical universities in Germany and provides an inspiring interdisciplinary environment at the interface of biology and engineering. The Systems Biology group combines mathematical modelling with state-of-the-art experimentation and is part of the newly founded Institute for Biomedical Genetics as well as the Stuttgart Research Center Systems Biology (SRCSB), one of the largest German inter-faculty infrastructures for systems biological research (https://www.srcsb.uni-stuttgart.de/). Your responsibilities
Develop quantitative models of gene expression providing mechanistic insights into perturbed proliferation and migration in cancer cells (see e.g., Strasen et al., Molecular Systems Biology 2018; Fritzsch et al., Molecular Systems Biology 2018; Bohn et al., PNAS 2023; Hartmann et al., Life Sci Alliance 2024)
Employ machine learning techniques and train kinetic models using quantitative experimental data (bulk and single-cell RNAseq, single-molecule RNA FISH, live-cell imaging and genome editing)
Conduct comprehensive data analyses, including transcriptomics, functional genomics and/or microscopy imaging
Collaborate closely with experimentalists and theoreticians within or outside the group
Participate in teaching in systems biology
Requirements
Master’s degree (or equivalent) in computational biology, bioinformatics, physics, mathematics, molecular biology, informatics, or a related field
Strong skills in programming and numerical computation, e.g., Matlab, Python, R or Julia
Enthusiasm for basic research questions and the ability to solve problems independently
Excellent communication skills and good team spirit
Fluency in spoken and written English
Experience in quantitative systems biology research is beneficial
We offer
A PhD student position initially for 3 years (65%, E13)
Interdisciplinary education within the SRCSB, the SimTech excellence cluster (https://www.simtech.uni-stuttgart.de/) and the Graduate Academy of the University of Stuttgart (https://www.gradus.uni-stuttgart.de/en/)
Professional training as an associated PhD with the newly funded DFG graduate school “EpiSignal - Crosstalk of intracellular signaling pathways and chromatin modification networks” (https://www.grk3112.uni-stuttgart.de/de/)
Priority access to high-performance computing resources
A vibrant, interdisciplinary, and collaborative research environment
The University of Stuttgart is one of the leading technical universities in Germany and provides an inspiring interdisciplinary environment at the interface of biology and engineering. The Systems Biology group combines mathematical modelling with state-of-the-art experimentation and is part of the newly founded Institute for Biomedical Genetics as well as the Stuttgart Research Center Systems Biology (SRCSB), one of the largest German inter-faculty infrastructures for systems biological research (https://www.srcsb.uni-stuttgart.de/). Your responsibilities
Develop quantitative models of gene expression providing mechanistic insights into perturbed proliferation and migration in cancer cells (see e.g., Strasen et al., Molecular Systems Biology 2018; Fritzsch et al., Molecular Systems Biology 2018; Bohn et al., PNAS 2023; Hartmann et al., Life Sci Alliance 2024)
Employ machine learning techniques and train kinetic models using quantitative experimental data (bulk and single-cell RNAseq, single-molecule RNA FISH, live-cell imaging and genome editing)
Conduct comprehensive data analyses, including transcriptomics, functional genomics and/or microscopy imaging
Collaborate closely with experimentalists and theoreticians within or outside the group
Participate in teaching in systems biology
Requirements
Master’s degree (or equivalent) in computational biology, bioinformatics, physics, mathematics, molecular biology, informatics, or a related field
Strong skills in programming and numerical computation, e.g., Matlab, Python, R or Julia
Enthusiasm for basic research questions and the ability to solve problems independently
Excellent communication skills and good team spirit
Fluency in spoken and written English
Experience in quantitative systems biology research is beneficial
We offer
A PhD student position initially for 3 years (65%, E13)
Interdisciplinary education within the SRCSB, the SimTech excellence cluster (https://www.simtech.uni-stuttgart.de/) and the Graduate Academy of the University of Stuttgart (https://www.gradus.uni-stuttgart.de/en/)
Professional training as an associated PhD with the newly funded DFG graduate school “EpiSignal - Crosstalk of intracellular signaling pathways and chromatin modification networks” (https://www.grk3112.uni-stuttgart.de/de/)
Priority access to high-performance computing resources
A vibrant, interdisciplinary, and collaborative research environment
Ref-Nr.: 9272497
Aktualisiert:
10.02.2026
Quelle: Bundesagentur für Arbeit
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weitere Infos Rechtliche Hinweise zur Nutzung
Ob die Stelle noch verfügbar ist und weitere Informationen findest du direkt auf der Website der Bundesagentur für Arbeit. Bitte beachte: OPROMA ist nicht der Anbieter dieser Stelle und kann keine Auskünfte geben.
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