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Bioinformatics Machine Learning Jobs in Texas (NOW HIRING)

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Bioinformatics Machine Learning information

What is a bioinformatics machine learning?

A Bioinformatics Machine Learning job involves applying machine learning techniques to analyze and interpret biological data, such as genomics, proteomics, and medical records. Professionals in this field develop algorithms, build predictive models, and enhance data-driven research in areas like personalized medicine and drug discovery. They work with large datasets, applying deep learning, neural networks, and other AI methods to extract meaningful insights. The role requires expertise in biology, statistics, and programming languages like Python or R.

What are the typical daily responsibilities for someone in a bioinformatics machine learning position?

In a Bioinformatics Machine Learning role, your daily tasks usually involve developing and tuning machine learning models to analyze large biological datasets, such as genomics or proteomics data. You'll collaborate closely with researchers, biologists, and data scientists to understand project goals, interpret results, and refine analytical approaches. Routine work includes coding, troubleshooting algorithms, visualizing data outputs, and documenting findings for internal teams or publication. The role often requires balancing independent analysis with teamwork and regular communication across disciplines, making it both technically challenging and highly collaborative.

What are the key skills and qualifications needed to thrive in the bioinformatics machine learning position, and why are they important?

A successful Bioinformatics Machine Learning professional needs a solid background in biology, statistics, and computer science, often backed by an advanced degree such as a Master's or PhD in bioinformatics, data science, or a related field. Proficiency with programming languages like Python or R, experience with machine learning libraries (e.g., TensorFlow, scikit-learn), and knowledge of version control systems are typical requirements, and relevant certifications can be beneficial. Strong problem-solving abilities, effective communication skills, and the capacity to work collaboratively in interdisciplinary teams set candidates apart. These skills are crucial for designing robust computational models, interpreting complex biological data, and translating findings into actionable insights in research or clinical settings.

Do bioinformatics machine learning professionals make a lot of money?

Bioinformatics machine learning professionals often earn competitive salaries due to the specialized skills in data analysis, programming, and biological sciences. Salaries vary based on experience, education, and location, but professionals in this field typically have higher earning potential compared to many other biotech roles. Advanced knowledge of tools like Python, R, and machine learning frameworks can also influence compensation levels.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Texas?

The most popular types of Bioinformatics Machine Learning jobs in Texas are:

What are popular job titles related to Bioinformatics Machine Learning jobs in Texas?

For Bioinformatics Machine Learning jobs in Texas, the most frequently searched job titles are:

Infographic showing various Bioinformatics Machine Learning job openings in Texas as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Postdoctoral Associate - Clinical Bioinformatics

Baylor College of Medicine

Houston, TX • On-site

$62K/yr

Full-time

Re-posted 7 days ago


Baylor College of Medicine rating

8.0

Company rating: 8.0 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

191st of 622 rated colleges and universities


Job description

Postdoctoral Associate - Clinical Bioinformatics
Division: Medicine
Work Arrangement: Onsite only
Location: Houston, TX
Salary Range: $62,232
FLSA Status: Exempt
Work Schedule: Monday - Friday, 8 a.m. - 5 p.m.
Summary
The lab is seeking a postdoctoral researcher to collaborate on groundbreaking projects integrating patient-level data with artificial intelligence (AI) and machine learning (ML) methodologies. The position involves annotating clinical data, collaborating with AI/ML/NLP teams, developing algorithms, and generating insights to improve patient care. The Postdoctoral Associate will write manuscripts, present research findings locally and nationally, and contribute to advancing clinical informatics.
Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.
Job Duties
  • Collaborates on the development of AI/ML/NLP-driven solutions for healthcare challenges.
  • Reads and interprets patient-level data to support the development of AI/ML/NLP algorithms for clinical applications.
  • Annotates medical notes and datasets to facilitate training and validation of predictive models.
  • Collaborates with data scientists, machine learning engineers, and clinical collaborators to design, implement, and validate innovative algorithms.
  • Conducts exploratory data analysis to extract meaningful insights from complex datasets.
  • Writes manuscripts and prepare presentations for local, national, and international conferences.
  • Conducts literature reviews and maintains awareness of advancements in bioinformatics, AI, and clinical data analysis.
  • Applies foundational knowledge of biostatistics and AI principles to inform study design and algorithm development.
  • Tests, debugs, and validates models in partnership with technical and clinical teams.
  • Ensures adherence to ethical guidelines for the use of patient data in research and development.
  • Works closely with the Artificial Intelligence in Health Lab (AIH-Lab) and the BD-STEP program to advance clinical informatics research.
  • Leverages clinical expertise to refine machine learning models, ensuring clinical relevance and accuracy.
  • Collaborates on the integration of clinical datasets into broader health informatics systems.
  • Provides expert annotations for training large language models (LLMs) and NLP algorithms, focusing on healthcare-specific use cases.
  • Presents findings in department meetings and seminars and support grant writing and funding initiatives.
  • Mentors trainees or junior team members in clinical informatics and research methods as needed.
  • Performs other job-related duties as assigned.

Minimum Qualifications
  • MD or Ph.D. in Basic Science, Health Science, or a related field.
  • No experience required.

Preferred Qualifications
  • MD passionate about clinical bioinformatics and driving innovation in healthcare.
  • Able to write manuscripts, present research findings locally and nationally, and contribute to advancing clinical informatics.
  • Background in basics statics.
  • Background in basics AI.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.
NN; PD; SN
Requisition ID: 25496

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