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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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) environments. Strong programming skills (e.g. TensorFlow, PyTorch, scikit-learn). AI/ML applications in life science. Large-scale data management (databases, data curation, metadata management, FAIR, etc
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KTH Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health Project description Third-cycle subject: Medical Technology (Joint KTH-KI program) In
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previous experience of the Spatial Transcriptomics method and data analysis as well as knowledge of the programming language R. The PhD student will be at KTH, Department of Gene Technology, SciLifeLab
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to build sequence dependent predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming
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. The research group is part of the National Program for Data-driven Life Science (DDLS), generously funded by the Knut and Alice Wallenberg Foundation: www.scilifelab.se/data-driven/ Our group focuses on studying
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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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strong publication record in relevant fields Proficiency in programming (e.g., R, Python, Bash) Effective communication in English is required for daily work. After the qualification requirements, great
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to teach in Swedish within three years, and if necessary, a language plan will be created in connection with the appointment as support. Eligibility Those eligible to be employed as associate professor
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degree in relevant fields (bioinformatics, immunology, computational biology, mathematics, and/or statistics). Strong programming skills in R and/or Python Demonstrated strong ability in analyzing high