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diseases. You will contribute to the acquisition of multi-omics data from cryopreserved patient-derived samples, working in close collaboration with clinicians to assess patient outcomes. You will present
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highlight the potential of microbiome intervention in immuno-oncology. In our team, we actively integrate translational data, functional assays and preclinical models, to understand and overcome mechanisms
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vehicle. Multiscale simulations of the downstream expansion behaviour of the residuals for different atmospheric layers. Definition of suitable interfaces to process data for the climate models. Expected
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, integrative biology approach that utilizes human pluripotent stem cell based model systems, high throughput functional genomic screening and big data based machine learning, bridging the scales from genetics
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status pursuant to the German Social Code IX (SGB IX) will receive priority for employment. Please submit your detailed application (including CV, cover letter, transcript of records, link to Master thesis
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information: Dr. Slavica Janevska | +49 3641 532-1188 Applications: Leibniz-HKI is proud to be an equal opportunity employer and promote diversity and inclusion in the workplace. It aims to increase
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relating the experimental data back to clinical datasets. We are an enthusiastic and international team and offer intensive training and mentoring. Your Tasks The successful candidate will have the
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and RNA-seq techniques (including data analysis) Cellular metabolism Mammalian tissue culture and cell manipulation Fluency in English (knowledge of German is not required) Our Offer: Scientifically
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
of strongest influence on the target properties. Moreover, the obtained data will be fed into a generative pre-trained transformer model (e. g. ChatGPT) to probe the potential of in-context learning for process
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sequencing, genome-wide data integration, statistical modeling, and hypothesis-driven experimental design, preparing them for leadership roles at the interface of molecular biology and data science. Your Tasks