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, complemented by publicly available data, to examine transcriptomic dependencies on transcription factor abundance and somatic mutations. These efforts aim to enable pan-cancer subtyping and uncover regulatory
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. Applicants must have a doctoral degree in geography, geoinformatics, computer science, data science, or a related field. Advanced PhD candidates are also encouraged to apply, however the appointee must have a
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. Applicants must have a doctoral degree in geography, geoinformatics, computer science, data science, or a related field. Advanced PhD candidates are also encouraged to apply, however the appointee must have a
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into regulatory mechanisms. The research will leverage a large in-house dataset from iCAN, complemented by publicly available data, to examine transcriptomic dependencies on transcription factor abundance and/or
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for microbiological research and antibacterial drug discovery. The work mostly comprises of using various microbiological methods (e.g. antibacterial susceptibility testing, biofilm assays), designing, developing and
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microbiological methods (e.g. antibacterial susceptibility testing, biofilm assays), designing, developing and validating new assays, and utilizing various laboratory instruments for automation and detection
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. The position is open to applicants with a PhD in computational biology, bioinformatics, biostatistics, cancer genomics, network science, or related fields. The appointment is a fulltime position and is made
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, cleanroom fabrication, performing cryogenic microwave measurements, and data analysis. You are expected to participate in advising and mentoring PhD students. Your experience and ambitions
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sensitivity of biosensors to improve existing sensors and to enable new technologies for a wide range of biomarkers and application areas. Skills, expertise and/or qualifications Doctoral degree (PhD
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should hold a PhD degree in molecular biology, biochemistry, cancer biology or related fields. Expertise in biochemistry, transcriptomics, NGS data analysis and basic programming in R/Python is a pre