Part-Time Bioinformatics Scientist (Contract/Consultant)
Genegeniedx Corporation
Pleasanton, CA, United States
3 months ago
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Role details
Contract type
Internship / Graduate position
Employment type
Part-time (≤ 32 hours)
Compensation
$104,000.0
Working hours
Regular working hours
Job source
Tech stack
Data Analysis
Bash Shell
Bioinformatics
Computational Biology
Computer Programming
Data Visualization
Python (Programming Language)
Machine Learning
Tensorflow
High Performance Computing
Pytorch
Large Language Models
+3 more
Deep Learning
Generative AI
Scikit Learn
Job description
We are seeking a highly skilled Part-Time Bioinformatics Scientist to support RNA-seq data analysis and machine learning model development for biomarker discovery and clinical diagnostics. This is a flexible role ideal for individuals seeking to contribute to cutting-edge translational genomics projects on a part-time basis. Key Responsibilities
- Analyze RNA-seq datasets, including preprocessing, QC, normalization, and differential expression analysis
- Develop and maintain bioinformatics pipelines for transcriptomic data
- Apply statistical and machine learning methods to identify diagnostic or predictive biomarkers
- Build and evaluate predictive models, including deep learning approaches
- Explore applications of large language models (LLMs) or multimodal AI in biological data analysis
- Collaborate with cross-functional teams to interpret results and guide experimental design
- Communicate findings through reports, visualizations, and presentations, + Opportunity to work on cutting-edge RNA-seq datasets from clinical samples
- Exposure to real-world biomarker discovery and diagnostic development
- Flexible, part-time engagement with meaningful scientific impact
- Collaboration with a highly experienced, multidisciplinary team
Requirements
- PhD candidate or PhD degree in Bioinformatics, Computational Biology, Biology, or a related field
- Hands-on experience with RNA-seq data analysis
- Strong programming skills in R and/or Python
- Familiarity with Linux/Unix environments and proficiency in bash scripting
-
Formal training in statistics and machine learning Preferred Qualifications
- Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
- Experience developing or applying deep learning models
- Familiarity with large language models (LLMs) or generative AI applications in biology
- Experience with NGS pipelines and tools (e.g., STAR, Salmon, nf-core, etc.)
- Experience working in high-performance computing (HPC) or cloud environments
- Strong data visualization and communication skills
Benefits & conditions
$50-$50
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