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Field
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this for data mining of existing scRNAseq datasets in the lab, as well as publicly published and newly generated data. You will study how abnormal genetic content modulates cell fate decisions in pluripotent stem
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assessment of materials using microbial communities Processing and analysis of high-throughput sequence data (DNA, RNA, community data, whole genome data, data mining) Data management for the division
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productivity data. Conducts extensive data mining and abstracting of faculty physician productivity data for reporting needs. Develops, refines, implements, and communicates enhancements to the Solution
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, with the possibility of a contract extension after this period. The selected candidate is expected to work on projects about dust control, biostabilization and bioleaching, and reuse of mine tailings
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highly efficient code bases. An interest or experience in working with imaging data. To be considered for this role, you must have: A PhD in Statistical Genetics, Machine Learning, Imaging Analysis, Human
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at the undergraduate and graduate level. Minimum Qualifications • The candidate should have completed their PhD in chemistry or a related field and have experience and interest in biotechnological production of natural
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learning. The post-holder will be familiar with the use of these techniques and experience of dataset construction and data mining will be essential. The successful applicant will have completed an MPhil/PhD
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Organisation Job description We are seeking a candidate for a fully funded PhD position for the project DeCODA-LM – funded through the stimuleringsbeurs scheme of the Faculty of Arts. The project
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GSMI - Postdoctoral Researcher - Plant Ecology and Soil-Plant Interactions in Vegetated Photovoltaic
Position Title: Postdoctoral researcher – Plant ecology and soil–plant interactions in vegetated photovoltaic systems-in mining site. Duration: 12 months, renewable. Position Summary: We are seeking
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care, social issues, text, and social media, and faculty members have developed key methodologies in data mining, social-network analysis and mathematical optimization. The department is also