PhD Student Position - Modeling the dynamics of cellular gene expression and decision making - Stuttgart

Universität Stuttgart

Raum Stuttgart

Dein Job

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/).

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

Dein Profil

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

Application procedure

Please send a single PDF file containing:

· A motivation letter including a description of previous research experiences

· A full CV

· A list of publications (if applicable)

· Scans of academic degrees (e.g. Abitur & Master degree)

· Contact details of two referees

Submit your application to legewie@ibmg.uni-stuttgart.de.

Starting date

As soon as possible

Closing date

Applications will be handled immediately but must be submitted by 31st of December 2025. Informal inquiries should be addressed to Stefan Legewie (legewie@ibmg.uni-stuttgart.de).

The University of Stuttgart has been certified as a family-friendly university since 2012 (http://www.uni-stuttgart.de/uniundfamilie/index.en.html) and wishes to increase the share of female academic staff and, for this reason, especially welcomes applications from women. Severely challenged applicants will be given preference in the case of equal qualifications.

Deine Benefits

Flexible Arbeitszeit

Stellenmerkmale

Dein Beschäftigungsumfang

Teilzeit (befristet)

Dein Gehalt

E13

Dein Arbeitsplatz:

vor Ort

Dein Büro:

Raum Stuttgart

Ansprechpartner:in

Bei Fragen

Herr Prof. Dr. Stefan Legewie

E-Mail

legewie@imbg.uni-stuttgart.de

Website

externer Link

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PhD Student*in - Modeling the dynamics of cellular gene expression and decision making

PhD Student*in - Modeling the dynamics of cellular gene expression and decision making