Human Gut Microbiome Data Analysis Intern

Role Overview: We are seeking a highly motivated and detail-oriented Human Gut Microbiome Data Analysis Intern to join our research team. The intern will assist in analyzing complex microbiome datasets to uncover insights into the human gut microbiome and its association with various health conditions. This is a unique opportunity to gain hands-on experience in a cutting-edge field and work alongside leading scientists. Responsibilities: Assist in the processing and analysis of high-throughput sequencing data from human gut microbiome samples. Perform statistical and bioinformatic analyses to identify patterns and associations in microbiome data. Develop and apply computational pipelines for microbiome data analysis. Visualize data using advanced graphing and plotting techniques to communicate findings effectively. Collaborate with the research team to interpret results and contribute to the preparation of scientific reports and publications. Stay updated with the latest research and methodologies in the field of microbiome science. Maintain detailed documentation of analyses and workflows. Qualifications: Currently pursuing or recently completed a degree in Bioinformatics, Computational Biology, Microbiology, Biostatistics, or a related field. Strong foundation in bioinformatics and statistical analysis, particularly in the context of microbiome research. Proficiency in programming languages such as Python, R, or MATLAB. Experience with bioinformatics tools and software for microbiome analysis (e.g., QIIME, mothur, DADA2). Familiarity with high-throughput sequencing data and techniques (e.g., 16S rRNA gene sequencing, metagenomics). Excellent problem-solving skills and attention to detail. Strong communication skills and ability to work collaboratively in a team environment. Prior research experience in microbiome science is a plus. What We Offer: Hands-on experience in a cutting-edge research environment. Mentorship from experienced scientists and researchers. Opportunity to contribute to impactful research with real-world applications. Flexible work hours and the possibility of remote work. Potential for future employment opportunities based on performance.