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Field
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Project Title: Integrating pharmacogenomics to support safe and appropriate psychotropic prescribing: a multi-methods approach to exploring the role of mental health pharmacists and developing
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Giacomo Marangoni, and embedded within the Policy Analysis section of the Multi-Actor Systems department. You'll collaborate with an interdisciplinary team working at the intersection of simulation
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. Your work environment You will carry out this research as part of the ERC-funded RIPPLE project, led by Professor Giacomo Marangoni, and embedded within the Policy Analysis section of the Multi-Actor
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to discover the fundamental mechanisms responsible for damage and deformation. About the host University and Through-life Engineering Services (TES) Centre Cranfield is an exclusively postgraduate university
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stressors. This transition reflects the need to acknowledge not just environmental factors but also the socio-economic and cultural contexts that shape vulnerability to heat. This research will employ a multi
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-oriented research to identify and translate core features of DIEs into design principles. Performing multi-case analysis of existing DIEs (e.g. SmartAgriHubs, FutureFoods, 4Growth) to assess organizational
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forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry. Read more: https://wasp-sweden.org/graduate-school/ As a PhD student, you devote
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or sorted cells, along with single-cell transcriptomics and spatial transcriptomics/proteomics datasets. You will collaborate with core facilities such as the VIB Single Cell Core and KU Leuven LISCO
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recordings from the Seismic Research Centre (SRC) at the University of the West Indies (1) and those to be collected in a large nodal deployment, the candidate will apply noise tomographic technique to reveal
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multi-center data challenges. Collaborating within Data Interpretation Task Forces (DITFs) to improve variant interpretation and assess the clinical relevance of both coding and non-coding variants