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high-priority condition as new disease-modifying therapies are developed. This PhD tackles a key diagnostic bottleneck in ADTKD-MUC1 and integrates precision genomic medicine into routine kidney care
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bioinformatic skills to predict the evolution of rare diseases? FSHD is a rare neuromuscular disorder. No approved treatment is currently available. Slow and variable disease progression complicate trial design
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at the Medical Faculty of Heidelberg University, in collaboration with Prof. Dr. Irmela Jeremias, invites applications for a PhD student in Bioinformatics / Computational Biology as part of the CRC1709-funded
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the Cardiovascular System”, the SFB1531 “Damage control by the stroma-vascular compartment” and the LOEWE Center “Lipid Space”. The Epigenetics/RNA working group, led by Prof. Ralf Brandes, is investigating how
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together with a PhD student in the lab of Prof. Jeroen Krijgsveld, which will focus on the proteomics part of the joint SFB/CRC project applying state-of-the-art proteomic approaches, e.g. low-input/single
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Forschungsgemeinschaft and the consortium SynThera funded by the Carl Zeiss Foundation (www.synthera.eu/ ). We are seeking two excellent and enthusiastic PhD students with a strong interest in microbiome research
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=25576 PhD student in cancer proteomics (m/f/d) Stellenanzeige merken Stellenanzeige teilen available
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cells, Ribo-seq, scRNA-seq, PDX in vivo models. The PhD student will work closely together with a PhD student in the lab of Prof. Michaela Frye, which will focus on the in vivo experiements of the joint
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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The overarching goal of the TOBI-team is to enhance precision cancer management through the development of innovative wet-lab and bioinformatic tools for diagnostic, prognostic, and predictive analysis. Prof