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Field
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processing & analysis (Python) We expect you to master the entire software development cycle, from analysis and design to programming, quality assurance, maintenance, documentation, and DevOps. We expect
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studies, such as online surveys and in-person experiments Desirable: • Backend development (Python, Ruby, …) • Linux system administration (deployment, networking) • Experience with decentralized/self
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science, embeddings and software agents is welcomed. The EBU-NEO tech-stack consists of: Python, LangChain, LangGraph, MongoDB, Milvus, Elastic Search. Knowledge from the fields of media science, user
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to network modelling, network theory and/or network meta-analyses. Fluency in programming as needed for network analyses (e.g., R/python) Strong analytical, organisational, and record-keeping skills
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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Excel, Word and PowerPoint. Strong organizational skills and able to work on multiple concurrent activities. Python programming experience is a plus. EXPERIENCE REQUIRED Undergraduate degree or equivalent
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field that provides a strong research background for the project. Fluency in English and Python are required. Research experience working with large-scale machine learning projects, extensive research
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) Experience with plant biochemistry, genetics and physiology Experience with bioinformatics and coding in Python or other programing language Experience with protein software tools like AlphaFold3, Boltz2
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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) Experience with plant biochemistry, genetics and physiology Experience with bioinformatics and coding in Python or other programing language Experience with protein software tools like AlphaFold3, Boltz2