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. * Strong background in numerical mathematics, modelling and simulation is required. * Knowledge in Inverse Problems. * Experience in programming (e.g., Matlab, C, Python). * A high level of competence in
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, Python, R, or related platforms for neural and behavioral data analysis. Experience developing independent research questions and pursuing external funding. APPOINTMENT TERMS This is a full-time, grant
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variant analysis, ideally in plants -genotype-environment association (GEA/EAA) or GWAS -programming in Python, with extensive experience working in Linux and multiple HPC environments. -population genomics
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required. Preferred Qualifications Strong coding experience using R and Python for data analysis. Expertise in the biological interpretation of multi-omics datasets (RNA-seq, proteomics, metabolomics, ChIP
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sequencing, bulk RNA-seq, and single-nucleus RNA/ATAC using R, python, command line interface and high-performance computing clusters Thorough documentation and communication of experiments and findings with
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Postdoc Position for Computational Genomics, AI Precision Oncology, Cancer Biology and Immunobiology
University of Pittsburgh, Pittsburgh , Pennsylvania, US | Pittsburgh, Pennsylvania | United States | about 2 months ago(Python, R, or equivalent). Experience with machine learning, multi-omics data analysis, cancer genomics, immunogenomics, or systems biology of transcriptional regulation is highly desirable. Subject 2
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Luxembourg Institute of Science and Technology (LIST) | Luxembourg, | Luxembourg | about 2 months ago
Proficiency in experimental design and statistical analysis Working knowledge of Python and/or AI/optimisation tools Language skills • Fluency in English, both oral and written. Other relevant
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languages such as R or Python. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range for this position is $72,879.00
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previous experience in theoretical quantum optics and quantum information, as well as strong skills in writing scientific papers. You are proficient in at least one common programming language such as Python
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large language models (LLMs), natural language processing (NLP), and/or machine learning, with a verifiable track record (e.g., publications, thesis, or open-source contributions). Proficiency in Python