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advance, CLASSIQUE focuses on a critical challenge: how to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https
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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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Qualifications Ph.D. in Bioinformatics, Computational Biology, Systems Biology, or a related field Proven experience in the analysis of single-cell or spatial omics datasets Strong programming skills in Python and
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(e.g., R, Python). Proven ability to publish at a high international level. It is a prerequisite that you are good at communicating in English. Strong collaborative skills and good collaboration skills
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background in thermodynamics and phase behavior of complex mixtures Excellent programming skills (e.g., Python, C++, Fortran, or similar) Experience with COSMO-based methods, including parameterization, model
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Stata; Knowledge of R, Matlab, Python, and/or Fortran; Experience working with micro data, ideally administrative or matched employer–employee data; Documented research track record at international level
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languages such as Python or R. Experience with machine learning, systems biology, or network modeling approaches. Previous expertise in human cardiometabolic or complex diseases, with domain expertise in but
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datasets. Proficient in Python and the various numerical packages (e.g. NumPy, Pandas, etc) Ability to work both independently and as a part of a team. Excellent communication and writing skills in English
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Quantification Python and ML frameworks (TensorFlow, PyTorch, JAX) Reproducible and open-science practices Experience with geospatial, environmental, or climate data is advantageous but not required. What We Offer
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Applications are invited for a position as postdoc in Computational Biology in the laboratory of DNRF Chair and Novo Nordisk Faculty Professor Vijay Tiwari (https://www.tiwarilab.org