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this Wellcome Trust-funded project, we will characterise the regulatory pathways of a panel of different G protein-coupled receptors (GPCRs) to explore how arrestins contribute to subcellular GPCR signalling
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of pre-existing and new eDNA metabarcoding datasets obtained in Australian coastal waters. Co-develop a new computational tool and/or indices for detecting early signals of marine ecosystem change. Lead
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the evaluation process. Failure to indicate the competition reference, the lack of any of the documents required in the application, or the sending/delivery of the application to a location other than that
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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | about 1 month ago
multidisciplinary team involving image processing labs (e.g., CMAP) and French hospitals (e.g., CHU Kremlin-Bicêtre, Hôpital Foch, Institut Mutualiste Montsouris, Institut Gustave Roussy). Phase 1: Design and develop
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Board. Payment is made on the 23rd of each month, through bank transfer to the Bank Identification Number of the fellow identified in the contracting process. Other benefits: Reimbursement of Voluntary
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-award courses of Higher Education Institutions. Preference factors: Machine Learning Knowledge. Knowledge of signal processing and machine learning libraries (e.g., PyCaret, scikit-learn). Minimum
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probability, partial differential equations, and mathematical physics. In statistics, these include biostatistics, optimal design, computer experiments, sequential analysis, shape-constrained inference, time
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of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have submitted
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, key terrestrial sedimentary sequences provide an opportunity for such studies. For example, shallowing-upwards emergence sequences deposited during glacioisostatic rebound indicate large-scale
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regular meetings with the research group. Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, or a related field. Proven experience working with LiDAR sensors, point cloud data