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the AIM-PACE project, which aims at developing a new generation of safe-and-sustainable-by-design, bio-based and circular plastics by combining AI, microbial technology, computer modelling, and polymer
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missing and incomplete symptom data can introduce bias and worsen existing inequalities. This PhD will develop innovative statistical and machine learning approaches to understand, model, and overcome
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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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, clinical data and AI-driven modelling for cancer research! In this role, you will bridge the gap between machine learning, computational biology, and haematological oncology. You do not need to arrive as an
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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neuroscience, brain circuit imaging and atlas mapping, and machine learning and AI - that will expand a cross-college team studying the brain circuits underlying craving, reward, and addiction. The hire will
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and Atlas Mapping. The position is one of four in a coordinated cluster hire - alongside colleagues in behavioral neuroscience, machine learning and AI, and research software engineering - studying
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of the project thereby complementing the human data analyses performed in Maastricht. Post-translationally modified proteins (PTMs) and their antibodies have been long-implicated in the etiology of auto-immune
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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About the project: Machine learning accelerated Inverse Design of Graphene Nanoribbons for Green Energy Supervisor: Dr Sara Sangtarash, University of Warwick Thermoelectric materials convert heat