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the development team of TreePPL (www.treeppl.org ), a universal probabilistic programming language and new software for phylogenetics. The successful candidate will be responsible for the user-interface aspects
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the documentation requirement for doctoral education . Skills and personal qualities Necessary Skills: Strong programming skills in languages such as Python. The ability to work both independently and collaboratively
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Program for Data-Driven Life Science (DDLS ) and the student joins its research program . Supervision: Associate Professor Hossein Azizpour What we offer Admission requirements To be admitted
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fields and access to various scientific and technical expertise. All PhD students at the Faculty of Medicine attend the doctoral education program. More information about the program can be found
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tools for end-to-end processing of next-generation sequencing data, from raw data to variant discovery (e.g., GATK pipeline). Experience with programming languages (e.g. bash, Python, and R). Experience
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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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an individual study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required. The research group The position is based in Joakim Dahlin’s team at Karolinska Institutet
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programming languages (e.g., Python, R). Experience working in a LINUX/UNIX environment. An excellent molecular biology skillset. Experience with NGS library preparation supported by a strong publication record
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efficiently interact in the interdisciplinary project. We seek candidates with a strong computer science, mathematics, statistics, or bioinformatics background and strong programming skills. Some previous
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National Program for Data Driven Life Science (DDLS). About the DDLS Fellows program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems