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spectroscopy Should have working knowledge of optics, electronics, 3D experimental design (e.g., CAD) and coding languages (e.g., Python) Should be willing to train users of spectroscopic and experimental
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models or glioblastoma research Familiarity with transcriptomic methods (RNA-seq, FISH, spatial transcriptomics) Programming skills for data analysis (Python, R, or MATLAB) Workplace Workplace We offer
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in R and Python (MATLAB experience is a plus) Ability to analyze high-dimensional bioinformatics datasets, including multi-omics data (e.g., transcriptomics, epigenomics, proteomics, spatial or single
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/Python). Familirarity with AI/ML methods for scientific computing and openness to explore different approaches Very good command of English is required (spoken and written) Additional Information Benefits
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Programming experience in python Interest in extreme weather phenomena Workplace Workplace We offer A fully funded PhD position at ETH Zurich within an SNSF Ambizione–funded project The opportunity to work
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modelling Experience developing or applying models of forest dynamics Experience working with ecological and multi-scale datasets Proficiency in scientific programming (e.g., R, Python, Rust, or similar
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computationally and developing scientific software. Experience in Python is highly recommended, additional knowledge of performance-oriented modeling frameworks, either based on Python (e.g., JAX, Pytorch) or other
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Python are essential Excellent teamwork, collaboration and communication skills Proficiency in written and spoken English A stimulating, challenging and multifaceted research environment Good integration
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(preferably Python), multiple years of programming experience as well as profound knowledge of professional computer-aided design and 3D modelling In addition, you have experience in CAD/CAM (preferably McNeel
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programming languages (e.g., MATLAB, R, or Python) Excellent communication skills You will have in-building access to mouse laboratories as well as access to state-of-the-art research equipment in metabolomics