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Field
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advantage: Developing algorithms for CFD solvers (e.g. OpenFOAM). Programming in C++ or Fortran and proficiency with MATLAB or Python scripting. Experience with tools for simulating chemical kinetic, e.g
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research outputs Data science skills, especially data analysis and prediction modelling Proven ability to write code in Python Experience working in a research team Excellent writing and communication skills
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towards histopathology and spatial sequencing experiments. Extract RNA/ DNA from tissues and prepare sequencing libraries. Analyze spatial sequencing data using Python or R. Perform rodent neurosurgeries
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scientific programming (Python) and deep learning frameworks. Fluent oral and written communication skills in English. Desired qualifications: Expertise in broader topics in computer science, information
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, bioinformatics or related discipline Strong computational skills, with expertise in scripting in BASH and either R or Python Experience with analysing complex datasets on high-performance compute clusters A track
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, molecular properties, and pathological images. Strong knowledge and experience in data science algorithms, methods, and analysis techniques. Experience in programming using Python and R languages and working
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open source geospatial packages under OSGeo; Experience in programming with multiple languages (e.g. Java, C/C++, Python) for geospatial information systems, agro-informatic applications, crop modeling
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experience using Python machine learning and large language models. Experience in machine learning and NLP for automated misinformation detection, social media data scraping and analysis, and human annotation
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EMS mutagenesis protocols in plants. Prior work involving biochar, soil amendments, or sustainable forestry applications. Experience with R, Python, or other bioinformatics tools for omics data analysis
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, python, or R) is critical. Strong organizational, leadership skills and passion for scientific discovery. Exceptional ability to work with a team as well as to work independently and be extremely self