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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | about 2 months ago
: The fellowship is legally governed by the Research Fellow Statute (Law no. 40/2004, of August 18), available at https://diariodarepublica.pt/dr/legislacao-consolidada/lei/2004-58216179 , and the Universidade NOVA
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assigned to research projects, available at the following website address: https://s.ua.es/es/nlJx , approved by the Governing Council of 22 December 2009 (BOUA of 15 January 2010), and with instructions
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TR333, SFB 1454, or iBehave). Expertise in proteomic analyses is desirable. In addition, the professorship is expected to actively contribute to conducting and further developing teaching within
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/open science, life sciences data systems, and analysis of various kinds of omics data (e.g., metabolomics, proteomics, genomics, transcriptomics, etc.). Postdoctoral research experience in an academic
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with a possibility of extension. Research Focus IMPRS-GS: Projects span experimental (genomics, transcriptomics, proteomics, etc.) and theoretical (bioinformatics, computational biology, etc
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
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https://www.science.org/content/article/metal-scaffolds-turn-bacteria-live-wires . [1] Postdoctoral fellow: high resolution microscopy and immunolabeling of conductive structures in multicellular cable
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bioinformatics Experience with analysing data from airway samples from patients with asthma Comprehensive understanding of T2 immunity in asthma Experience with airway proteomics and transcriptomics Desirable
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Regenerative Medicine Postdoc Appointment Term: 1 year initially and renewable. Appointment Start Date: Immediately available but flexible Group or Departmental Website: http://www.liwanglab.org (link is
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research. The main purpose of this position is to analyze the metabolomics data that we generate, as well as complementary, available genomic or proteomic data for several projects focused on understanding