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Field
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multi-modal perception and machine learning. Current noninvasive agricultural monitoring systems rely primarily on passive sensing, which limits sensitivity to early-stage plant stress. This project
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matter’ of biology, under-studied owing to the historical lack of preparative and analytical tools to probe the local molecular composition and transient interactions of molecules within glycocalyces, and
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learning (vocational competence, workplace learning, assessment) Doctoral candidates have the freedom to design a dissertation project related to these themes. Mandatory courses and participation in regular
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value chains to enable AI-based applications, using methods and models from e.g. operations research, data analytics or artificial intelligence/machine learning. Identify, structure and prioritise
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analytical skills and can work independently, structured and carefully. Interest and ability to learn and apply new methods and working methods is also a requirement. You should also have a high degree of
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of formulating them, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment
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demonstrate the ability and eagerness to learn new methods and a strong interest in developing both experimental and analytical skills. On a personal level, we are looking for a collaborative and engaged
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perturbation-based GRN inference for single-cell and spatial multi-omics data, to boost GRN quality and add the cell type and tissue heterogeneity dimensions to causal regulatory analysis. A deep learning
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learn experimental and computational approaches to tackle fundamental biological questions with medical relevance using innovative system-wide techniques. You will work on an exciting multidisciplinary
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17 Feb 2026 Job Information Organisation/Company Chalmers University of Technology Research Field Biological sciences » Biology Biological sciences » Other Chemistry » Analytical chemistry Chemistry