Research Scientist (f/m/x) in Spatial Multi-Omics Analysis

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Testo originale dell'annuncio (in inglese)

Area of research: Scientific / postdoctoral posts Job description: Research Scientist (f/m/x) in Spatial Multi-Omics Analysis 103012 Full time, close to full time 27,3 - 39 hrs./week Neuherberg near Munich Partial Home Office possible At Helmholtz Munich, we develop groundbreaking solutions for a healthier society in a rapidly changing world. We believe that diverse perspectives drive innovation. Through strong partnerships, we accelerate the transfer of new ideas from the lab to real-life applications, improving lives. Spatial multi-­omics technologies are currently pushing the boundaries of single-cell profiling techniques. By measuring the position of every cell alongside multiple views of cellular activity, these technologies promise to deliver crucial insights to ­understand tissue function and regulation, especially in diseases with distinct spatial patterning such as lung cancer. The Core Facility Bioinformatics and Statistics (CF-BIOS) at Helmholtz Munich is part of the SPACETIME project, an EU consortium studying how spatial cellular organization changes with disease severity in non-small cell lung carcinoma. CF-BIOS provides comprehensive bioinformatics and statistical support for diverse research applications. We work closely with data-generating facilities and on-campus computational groups to deliver integrated, high-quality workflows. Our services include the analysis of a broad range of omics datasets, including single-cell, spatial and multi-omics applications, as well as supporting large cohort studies. The research scientist position (f/m/x) is embedded within CF-BIOS and you will work closely with the SPACETIME consortium members and the data analyst team at Helmholtz Munich. The focus of the role will be the analysis of spatial transcriptomics and multi-omics data generated within SPACETIME. Responsibilities include data management, metadata collection and validation, generation of reproducible analysis playbooks, developing and delivering training and documentation for spatial analyses, development of applications and infrastructure to enable and support meta data collection and data accessibility and exploration and visualization across the consortium. If you like to be part of a dynamic team and work at the cutting edge of science, this full-time position (39 hrs./week, or if part-time minimum 70%) may be for you. Your tasks Ensuring reproducible analysis workflows for spatial multi-omics data in close collaboration with a team of analysts Data management, meta data annotation and validation Design, implementation and evaluation of AI-driven tools and applications to facilitate data dissemination and access Supporting data processing and analysis, reusable workflow development, documentation, and user training Your profile Master or PhD in informatics, bioinformatics, engineering, or related fields with corresponding work experience Strong programming skills (R, Python, Bash), versioning (Git) Demonstrable experience analyzing data from various next-generation sequencing technologies, especially single cell sequencing and spatial- and multi-omics technologies Experience with data management, metadata annotation, and with the use of high-performance computing environments Team-oriented, proactive, service mindset with strong communication skills, as well as english language proficiency Desirable experience with (considered as a plus) Linux server and storage administration Developing and deploying multi-user software applications using modern programming frameworks Performing complex spatial biology and multi-omics analyses Delivering training courses and developing educational materials What we offer Opportunity to work within a large EU-funded international consortium Access to cutting-edge spatial transcriptomics and multi-omics datasets Collaboration with leading researchers in lung cancer and spatial biology Join an interdisciplinary, dynamic team with short decision-making paths and a collaborative