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on bioinformatics analysis of spatial gene expression data as well as other modalities (i.e. microbiome; metabolites, proteins) generated using the Spatial Transcriptomics (ST) method, Spatial metaTranscriptomics
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, 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 focuses
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repertoires, recombinant antibody development, and immunochemical analysis to study the evolution of such responses during therapy, in combination with assessment of clinical outcomes of the therapy to define
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visualization and scientific communication Extensive knowledge of relevant machine learning and AI techniques Exceptional collaborative abilities Self-motivated individual with ability to work independently
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and integrative (proteo-)omics expertise in the lab, guided by leading experts in terminomics, systems-level data analysis, and structural bioinformatics. Your profile A PhD in biology, biochemistry
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, physics and materials science. Scientists with expertise in biophysical methods of interaction analysis are responsible for a facility belonging to SciLifeLab, part of a national infrastructure for research
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. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in time and space, how this affects
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Comprehensive skills in data analysis and bioinformatics Proficiency in programming with Python Proficiency in version control (Git, GitHub) Meriting criteria are: Experience in mechanistic and ODE-based
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learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include: Development of ML/DL methods for multi-omics data analysis. Design and implementation