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Field
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are seeking a highly motivated Postdoctoral Fellow with strong expertise in RNA-seq and multi-omics data analysis. Candidates should be proficient in Python and/or R and have a solid background in Biology
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students and working effectively in a team-based research environment Proficiency in common computational chemistry software and coding techniques e.g. Gaussian/Amber/Schrödinger/python/bash For more
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pipelines for genomic data analysis, and of programming languages such as R, Python, or Bash script is essential, as is experience of working with High Performance Computing. Time management skills
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, analytics, and software development, ideally using tools such as Python or similar platforms. Experience developing dashboards or visualisation platforms (e.g. Grafana, Power BI, or web-based frameworks
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Fellow will strengthen our analytic capabilities by using Python and AI-enabled methods to extract, classify, and summarize insights from unstructured data, including text, images, and other digital
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electrophysiology (neural recording, EMG, or related techniques) Exposure to sensor design, bioinstrumentation, or embedded systems Programming experience (e.g., MATLAB, Python, or similar for data acquisition
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histology/ flow cytometry methods, familiarity with CRISPR/Cas9 or other genetic perturbation approaches* For computational scientist : previous experience with NGS data analysis; fluency in R, Python or C
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skills: Experience in statistical programming in languages such as R (ideal) or Python. An understanding of linear models and probability. A background in biology, with a preference for cellular biology
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robotics) for field-based phenotyping Data management and analytics from multi-stream remote sensing platforms Preferred willingness to learn: Use of Python, CRBasic, Matlab, C++, R, or other programming
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by 9/1/2026. Preferred skills: Experience in process-based crop, soil, or hydrological modeling. Proficiency in Python and other programming languages (Fortran and C/C++ are a plus). Familiarity with