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The Department of Biotechnology and Food Science, Institute of Computational Biology is currently seeking a Postdoctoral Research Associate (Reference code 216) Extent of employment: 40 hours per
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environments (e.g., Mininet, NS-3), MANO platforms (e.g. OSM) Solid understanding of 5G/6G network architectures and technologies is considered a strong asset Proven software engineering and coding skills (e.g
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). Apply good practice for version control, documentation, and data governance (Git, code review, metadata) to enable collaboration with colleagues, students, and partners. Location: The incumbent will be
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, collaborating with experimental partners on validation, maintaining clear and reproducible code and documentation, and communicating findings through presentations, manuscripts, and contributions to grant
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, biomedical engineering, or a related field. • Experience with coding software such as Python, R, or Matlab. • Familiarity with collaborative coding software such as GitHub and database management
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neurodifferentiation and cancer models. Candidates with strong interest in gene regulation, chromatin architecture, epigenetic mechanisms, and non-coding RNA biology are encouraged to apply. Experience in performing and
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. Description We are looking for a postdoctoral computational biologist to decipher the genomic regulatory code controlling gene expression in plants. Within the ERC-funded multiCODE project, we aim to unravel
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. Description We are looking for a postdoctoral molecular biologist to decipher the regulatory code controlling gene expression in plants through the engineering and large-scale validation of synthetic promoters
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Networks, and ICT Services & Applications. Your role The APSIA Group (Applied Security and Information Assurance), led by Prof. Peter Y A Ryan, has recently been granted the project "Quantum LDPC codes with
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, pharmacogenomics, statistical genetics, or population genetics and experience in statistical and computational analyses of high-throughput omics data Ability to code in one or more scientific programming languages