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of high-dimensional data (e.g., single-cell RNA-seq, phylogenetics, spatial data) Experience in R or Python Application instructions: Please send a CV, a brief cover letter describing your research
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essential. Experience with MATLAB or Python computer programming for neuroimaging data analysis is essential. Experience in MRI and/or EEG acquisition and analysis is desirable. Experience working on research
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experience in machine learning methods, tools, and platforms. Proficiency in Python, with demonstrated software development experience. Hands-on experience in MLOps, including the design and deployment
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programming languages (e.g., R, Python). Successful applicants should be self-motivated, well-organized, and able to work independently and collaboratively. Excellent written and oral communication skills
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with experience in One Health or climate-health research. Proficiency in systematic reviews, survey methods, and/or causal inference is essential, along with programming skills (e.g., in R or Python
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.). Strong programming skills in Python, C/C++, and experience with data-centric control and monitoring architectures. Knowledge on standard communication protocols for smart grid interoperability, such as IEC
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/ NiFi/ Knime, Programming in Python and SQL. Experience with version control systems (Git, CI/CD); Java/Scala is a plus. Familiarity with containerisation and orchestration like Docker and Kubernetes
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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;Knowledge of bioinformatics tools relevant to gene editing and transcriptomics (e.g., Benchling, SnapGene, Geneious, R, Python);Proven track record in publication and in scientific outreach. Personal Skills
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skills in C/C++ and Python Relevant experience in deep reinforcement learning A proactive attitude towards achieving research excellence Demonstrated commitment, teamwork abilities, and critical thinking