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Field
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visualizing large-scale, complex data. For the vacant position, we particularly search for a colleague experienced in computational text and/or image analysis and processing platform data. Your future tasks
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is to analyse the metabolic diversity of a large number of species in the garden using mass spectrometry-based metabolomics, following standardised procedures. The postdoctoral researcher will be
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demonstrate equivalent research experience and qualifications. Experience in both wet-lab and dry-lab research is beneficial. You must have expertise in analysis of large-scale genomic data and confidence in R
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directly guide functional validation studies performed by a second postdoctoral researcher using advanced human brain organoid models in the Artegiani-Hendriks group. The project is embedded within a large
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for better training and novel network designs. Low Effective-dimensional Learning Models. We will extend foundational theory of how large ML systems can be regularised to have dramatically fewer trainable
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structure – function relationships in lipid systems for drug delivery (predominantly lipid nanoparticles). The group has extensive expertise using large scale research infrastructures to study lipid systems
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population genomic analyses of crop species Experience managing and analyzing large-scale biological datasets Experience using SLURM-based high-performance computing systems Demonstrated proficiency in R
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Project Overview Wafer-Scale Integrated Sensing Devices based on Optoelectronic Metasurfaces (WISDOM) focuses on semiconductor wafer growth and processing for photonic applications. This program
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sequence alignment methods is a plus. You will focus on developing efficient indexing methods for the analysis of large-scale DNA sequence data. Research project 2. This interdisciplinary project focuses
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such target pairs at scale remain very limited, creating substantial scope for discovery. Our integrated wet-dry lab is particularly well positioned to move prioritized candidates through experimental