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Field
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the research focus of the RTG 2633, a multidisciplinary program with expertise spanning basic sciences, including immunology, genetics, biostatistics, bioinformatics, systems medicine, anatomy, nutrition
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), immunofluorescence and microscopy Prior experience in RNA biology, NGS and/or Metabolism is an asset Understanding of common bioinformatics approaches and experience with one of the main programming languages for data
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Immonuprecipitation (ChIP); Genome editing, e.g. to (degron) tag proteins of interest; Bioinformatic analysis of generated sequencing data. During your PhD, you will learn about the field of gene regulation, expand our
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transcriptomics Present findings at conferences and publish in peer-reviewed journals Your qualifications and skills: You hold a Master’s degree (or equivalent) in Bioinformatics, Data Science, Systems Biology or
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• Training courses in cutting-edge technologies (OMICS technologies, innovative human infectious disease models (e.g. organoids, iPSC), bioinformatics, AI) and soft skills required for a successful career
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discipline Solid wet-lab experience in molecular biology, ideally with tissue or protein work Motivation to develop bioinformatics and data analysis skills (training provided) Proficiency in English (spoken
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culturing, etc.) Strong interest in phage biology & antimicrobial resistance Preferred: Experience with omics data analysis (esp. RNA-seq, proteomics) Bioinformatics tools and computational skills (R/Python
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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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clinical management. We are seeking a non-clinical PhD candidate with high-level bioinformatics skills to join our internationally renowned, multi-disciplinary team in Newcastle. This position provides
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: 29.07.2025 Limitation:Temporary (2 Jahre, Verlängerung angestrebt) Contract:TV-L Your tasks Single-cell multiomics in primary cells: wet-lab experiments and performing bioinformatic analyzes on the single-cell