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Field
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candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics
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Qualifications The following qualifications and experience will be considered an advantage: Experience with crop modeling. Experience with plant breeding. Background in data science, machine learning, and
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required to meet the eligibility criteria. Of secondary importance are: Experience with Python and relevant libraries for machine learning, optimization and simulation. Documented expertise in simulation
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at the interface of automatic control, electrochemistry, and machine learning. The position will also involve close collaboration with another postdoctoral researcher working on a complementary project in physics
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for a postdoctoral position in plant cell wall dynamics and mechanochemical signalling. The expected starting date is September 2026 or according to agreement. Umeå Plant Science Centre (UPSC) is one
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data and multimodal datasets combining imaging and molecular measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with
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domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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. Required qualifications: PhD in a field such as physics, systems biology, applied mathematics, machine learning, or related fields. Strong programming skills (e.g. Python) and experience with modern ML