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in epidemiology, research, and statistics Well-versed in R/R Studio, SAS, Microsoft Suite Knowledge of SQL and Python Point of Contact Rachel Eligibility Requirements Citizenship: U.S. Citizen Only
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in the one of the relevant fields. Preferred Skills: Strong skills in data analysis and database management; statistics and programming knowledge preferred (e.g. R/R Studio, SAS, Stata, SQL, Python
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confident in handling the relevant data and be competent in programming on either MATLAB or Python. You will also be enthusiastic about building and troubleshooting your experimental rig. You will have the
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 1 month ago
will be carried out in INEGI or FEUP facilities in Porto. 4. Academic Qualifications: Master’s degree in mechanical engineering. Proficient knowledge of programming languages such as Python or others
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the team and the customers. Be self-directed to fulfil the project requirements. Job Requirements: Competence in working with languages such as C along with Python-based coding and AI development. Have a
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datasets (e.g., GWAS, RNA-seq) Proficiency in programming languages such as R or Python and experience with bioinformatics tools Strong planning and organising skills Excellent written and verbal
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. • Proficiency in software development in R/Python. • Experience with high-dimensional mixed data types or integrative methodologies is desirable. Application Instructions Please submit the following materials
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, Google Cloud, Microsoft Azure), including containerization (Docker), orchestration (Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine
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scripting in and performing data analysis in Python Proficiency in running laboratory and field experiments Req ID: 32513 Apply now
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interactions Expertise with human in vitro co-culture models, including CD8+ T-cell responses, is desirable Expertise in omics and systems immunology Proficiency in R or Python programming for data analysis