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science. The successful candidate will develop innovative methods and models to decode the language of the genome and advance our understanding of how genetic variation contributes to complex diseases
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systems, statistical physics and machine learning, and using these insights to develop new methods, with the support of competent and friendly colleagues in an international environment? Are you looking
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
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to achieve scalability in terms of the simulator systems. The work will be done in close collaboration with the physics team to be able to develop optimizations also at the algorithmic level in a co-design way
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global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally
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well as about 70 employees, including three professors and ten associate professors. The department is a dynamic and international work environment with well-developed collaboration with Swedish, Nordic, and
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to make a difference. Do you want to be involved and contribute to our development? Together, we can create a sustainable future through knowledge and innovation. We believe that knowledge and new
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methods that reduce compute, energy usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and
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. The role involves contributing to this research project with a focus on model development, implementation, and testing. Further tasks involve dataset curation, analyzing results, and the creation
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, perform simulation studies, and apply developed methods to empirical datasets. The positions do not involve any lab work. The work includes mathematical modeling, algorithm development, statistical analysis