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Field
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, immunoprecipitation and confocal microscopy. Experience with cancer organoid models and/or bioinformatics is an advantage. We offer broad training possibilities in the required experimental methods within a stimulating
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of bioinformatics (RNA-seq pipelines, Python/R) and sequencing technologies (nanopore, single-cell, ATAC/ChIP-seq). Knowledge of genetic regulation and lncRNA function in immune contexts Excellent data analysis and
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chemistry, biochemistry, molecular genetics, bioinformatics and advanced technology development. Through their direct association with established medical research centers (NeuroSysMed with a focus on
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Python, TensorFlow, PyTorch, or similar frameworks. MS or higher degree (PhD preferred) degree in Computational Neuroscience, Computer Science, Bioinformatics, or a related field with demonstrated ability
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, neuroimaging, neurophysiology, proteomics, transcriptomics, epigenomics, metabolomics, bioinformatics, cell models and animal models. First in man and Phase 2, 3 and 4 clinical trials are also strongly supported
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· Strong skills in cell culture and/or C. elegans culture. · Proven success in publishing research papers. · Expertise in virology is a plus. · Expertise in bioinformatics is a plus. Special Instructions
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and present at scientific conferences Qualifications Basic Qualifications PhD in Computational Biology, Bioinformatics, Computer Science, Human Genetics, Toxicology, or related field (summer and fall
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found online: https://www.jglab.org/ and www.github.com/goekelab Requirements: PhD in Bioinformatics, Computer Science, Statistics, Genomics, or a related discipline Good programming skills and strong
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, or related approaches. Hands-on experience in high-throughput screening techniques for protein interactions and degradation pathways. Familiarity with computational tools for data analysis and bioinformatics
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models with a key focus on integrating pathology, radiology, and electronic health records (EHRs), while collaborating with the bioinformatics team to incorporate molecular data such as bulk RNA-Seq, whole