Bioinformatics Support Specialist

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The Ismagilov Lab at Caltech is hiring a full-time Bioinformatics Support Specialist for a 2-year term position. Reporting to Professor Rustem Ismagilov, the successful candidate will contribute to the lab’s key projects and collaborations in human health, which include: developing novel tools that improve biological AI models by orders of magnitude; developing closed-loop systems that combine robotics and AI for rapid autonomous experimentation; discovering in human tissues novel bacteria, fungi and viruses (and corresponding genes and pathways) responsible for heath and disease; developing novel diagnostic approaches; understanding microbial origins of human diseases.  Additional details about the lab can be found at http://ismagilovlab.caltech.edu/  

• Assist graduate students, postdocs, and research staff with bioinformatics/computational components of all ongoing projects.
• Contribute to manuscript preparation and grant proposals, data visualization, and scientific presentations.
• A highly motivated and qualified candidate may additionally develop their own independent aspects of ongoing projects.

• Learn and apply state-of-the-art statistical and computational methods for analyzing datasets from shotgun metagenomics, amplicon sequencing, and RNA-sequencing experiments.
• Assist in the design, implementation, and benchmarking of in-silico experiments.
• Generate computational results and publication-quality figures for clear communication of results to lab members and external collaborators.

• Collaborate with lab members and external colleagues to learn and implement best practice methods and packages for data analysis and processing in the lab.
• Work with lab members to understand needed bioinformatic capabilities and develop tools to accomplish them.
• Work with lab members and external collaborators to help them develop, execute, and maintain state-of-the-art data processing pipelines on Caltech high-performance computing (HPC) clusters.
• Develop and maintain scripts for routine analysis tasks such as qPCR quantification.
• Develop and maintain scripts for automated robotic platforms to perform laboratory procedures.
• Help lab members test and integrate LLM-based AI tools to improve efficiency of research tasks such as experimental design and technical writing.

• Maintain well-organized computational workspaces, including data storage, version-control systems, containerization, and documentation in a neat, detailed electronic lab notebook.
• Maintain reference databases of microbial genomes, gene clusters, antimicrobial resistance markers, and metabolic pathways.
• Maintain organized and version-controlled repositories and containerized computational environments (Docker/Conda), using Python and/or R.
• Assist with data management on remote computing clusters and back-up servers, including organizing raw and processed data, maintaining version control, and ensuring data integrity and reproducibility.

• Experience with programming languages for scripting and data analysis: Python, R, and Bash required.
• Bachelor’s degree in science with educational emphasis in computational sciences, bioinformatics, biology, microbiology, computer science, bioinformatics, computational biology, data science, or a related field required at time of application.
• Familiarity with basic molecular biology topics.
• Experience (including coursework or internships) in data analysis using at least one scripting or programming language (e.g., Python, MATLAB, R).
• Experience working with next generation sequencing data and/or big data (e.g. genomics, RNA-seq, single-cell RNA-seq, epigenomics, proteomics, metabolomics, etc.).
• Experience working in Linux/Unix environments.
• Strong drive to learn and to make positive impacts on the lab and lab’s mission. 
• Ability and desire to collaborate and support collaborative projects. 
• Highly detail-oriented; must have examples of well-documented code (e.g., Git repositories) involving complex technical tasks or data analyses available upon request.
• Ability to rapidly learn technical skills, particularly in computational methods and bioinformatic workflows.
• Strong organizational, time-management, and project-management skills; ability to professionally and continuously communicate priorities, workload, and current progress to all lab members.
• Must be able to use sound judgment to handle multiple simultaneous tasks, prioritize effectively, and troubleshoot problems independently.
• Must be able to work independently as well as part of a collaborative team in a dynamic, fast-paced environment.
• Ability to write clean, well-documented, and reproducible code for data processing and analysis.
• Ambition to develop research skills and advance scientific understanding through high-quality computational analyses and interpretation of biological data. 

• Experience with cloud computing environments (e.g., AWS, Google Cloud, or institutional equivalents) and using High-Performance Computing (HPC) clusters with the Slurm workload manager.
• Experience performing bioinformatic analyses involving shotgun metagenomics, RNA sequencing, or 16S rRNA gene sequencing.
• Experience with workflow management systems for pipeline automation (e.g., Snakemake, Nextflow)
• Proficiency with Git for collaborative coding, project tracking, and version control.
• Experience performing statistical analyses or modeling of complex biological datasets.
• Experience with containerization (Docker, Conda, Singularity).
• Experience creating visualizations or interactive notebooks (e.g., Jupyter, R Markdown, Dash).
• Experience fine-tuning LLMs for analysis or writing tasks.
• Co-authorship on a scientific publication.
• Solid understanding of statistical analysis methods (NHST, probability distributions, etc.)
• Ambition to pursue advanced training or career in computational biology, bioinformatics, ambition to enter a top medical or graduate school or a similar high-performance, high-impact environment in industry or academia.

• Resume (describe relevant experiences and accomplishments).
• Cover letter with specific examples demonstrating a) candidate’s alignment with lab’s mission, b) candidate’s level of ambition, motivation, and drive; c) candidate’s attention to detail and ability to produce data others can trust; d) the level of technical mastery of the top three most relevant experimental skills described in the resume.
• GitHub (preferred) or code examples.