Bioinformatics Analyst I

Baylor College of Medicine

Houston, TX

ID: 7311631 (Ref.No. 22931-en_US)
Posted: Newly posted

Job Description

Summary

The Cuddapah lab is seeking a highly motivated Bioinformatics Analyst I to join his lab at Baylor College of Medicine on an NIH-funded project at the intersection of neurodevelopmental disorders, sleep, and circadian biology. The Cuddapah Lab will be implementing machine learning and multi-omics approaches to explore molecular mechanisms driving neurodevelopmental diseases.
The Bioinformatics Analyst will take a lead role in implementing and developing computational tools and applying statistical methods to analyze high-resolution behavioral videos as well as single-cell RNA sequencing, proteomics, lipidomics, and other omics datasets. This is a unique opportunity to contribute to biomedical research in a collaborative and intellectually stimulating environment.

Job Duties

  • Engineers and refines predictive models and algorithms that will inform clinical choices, guide business strategy.
  • Assists in research initiatives aimed at identifying novel genes associated with diseases.
  • Translates complex data into actionable insights, presents these findings to key stakeholders through clear and compells visualizations and presentations.
  • Tracks and assesses the efficacy of the predictive models and algorithms. Suggests and implements enhancements whenever necessary.
  • Remains at the forefront of data science and machine learning advancements. Integrates the latest methodologies and innovations to address tangible challenges in the field.
  • Analyzes high-throughput datasets, including single-cell transcriptomics, proteomics, and lipidomics.
  • Develops and implements machine learning models to extract behavioral phenotypes from video recordings.
  • Designs, maintains, and documents reproducible computational pipelines using Python and related tools.
  • Collaborates with experimental scientists and clinical researchers to integrate multi-omics datasets and generates biological insights.
  • Contributes to the preparation of figures, methods, and data summaries for manuscripts, presentations, and grant applications.
  • Stays up to date with emerging tools and methods in bioinformatics, single-cell analysis, and artificial intelligence.

Minimum Qualifications

  • Bachelor's degree in Genetics, Biology, Bioinformatics, Biostatistics, Computational Biology, Computer Science, or a related field.
  • No experience required.

Preferred Qualifications

  • Master’s degree in Bioinformatics, Computational Biology, Computer Science, or a related discipline.
  • Experience analyzing high-throughput biological data (e.g., single-cell, proteomics, lipidomics).
  • Experience contributing to peer-reviewed publications in computational or biomedical research.
  • Proficiency with Python libraries such as NumPy.
  • Familiarity with machine learning, video analysis, or other data-intensive approaches in neuroscience or systems biology.
  • Experience with data analysis tools such as SQL, Tableau, or Power BI.
  • Has strong communication and collaboration skills.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.



Baylor College of Medicine fosters diversity among its students, trainees, faculty and staff as a prerequisite to accomplishing our institutional mission, and setting standards for excellence in training healthcare providers and biomedical scientists, promoting scientific innovation, and providing patient-centered care. - Diversity, respect, and inclusiveness create an environment that is conducive to academic excellence, and strengthens our institution by increasing talent, encouraging creativity, and ensuring a broader perspective. - Diversity helps position Baylor to reduce disparities in health and healthcare access and to better address the needs of the community we serve. - Baylor is committed to recruiting and retaining outstanding students, trainees, faculty and staff from diverse backgrounds by providing a welcoming, supportive learning environment for all members of the Baylor community.