Omniscius Consulting
Computer Programmer
Omniscius Consulting, Bethesda, Maryland, us, 20811
Our client is seeking a Computer Programmer with strong experience in machine learning, statistical modeling, and software development to support research efforts at the National Institute of Mental Health (NIMH). This role requires expertise in data science, computational biology, and the development of scientific applications to optimize the extraction and analysis of multivariate datasets. The ideal candidate will leverage cutting-edge technologies, such as Python, R, MATLAB, and PostgreSQL, to implement data-driven solutions that enhance biomedical research and decision-making processes.
This is a hybrid position which requires time onsite in Bethesda, MD.Key Responsibilities:
Develop, test, and refine novel programming methods, toolkits, and algorithms for bioinformatics and computational biology applications.Provide statistical modeling, server management, database management, and data visualization using tools like Python, R, Shiny, and MATLAB.Implement scientific applications to analyze complex datasets, including time series, genomics, and behavioral data.Design and optimize data processing pipelines for efficient data extraction, pre-processing, and visualization.Collaborate with researchers to apply computational techniques for biostatistics and statistical modeling across a variety of applications.Manage and maintain Linux-based (Debian) repositories and data storage systems for laboratory protocols and experimental data.Provide database support and maintenance to ensure data integrity, correction, and optimization using relational databases (PostgreSQL, MySQL).Develop and deploy dynamic web applications for bioinformatics, using modern technology stacks and cloud solutions.Qualifications:Education : Master's or Ph.D. in Computer Science, Data Science, Bioinformatics, Neuroscience, or a related field.Experience : Minimum 3 years of hands-on experience in data science, statistical modeling, machine learning, or bioinformatics.Programming Languages : Expertise in Python, R, Shiny, MATLAB, SQL, and GitHub.Data Science Tools : Proficiency with TensorFlow, PyTorch, scikit-learn, and XGBoost.Database Systems : Strong knowledge of PostgreSQL, MySQL, and experience with ETL processes and multivariate data extraction.Data Visualization : Experience with Tableau, Power BI, or other visualization platforms.Operating Systems : Proficient in Linux, especially Debian, for managing scientific data repositories.Machine Learning & AI : Applied experience with deep learning models, neural networks, and natural language processing (NLP).Collaborative Skills : Ability to work across teams to support research staff, troubleshoot technical issues, and provide bioinformatics solutions.Preferred Skills:Experience in developing scientific applications for bioinformatics research, including transcriptomics and genomics.Familiarity with cloud-based platforms like AWS or GCP for deploying machine learning models and managing large datasets.Experience working in a research environment, especially supporting data-driven biomedical research projects.Knowledge of high-performance computing (HPC) for bioinformatics data processing.Key Contributions:Create innovative AI and data science solutions to support bioinformatics research.Collaborate with researchers to solve complex scientific problems through the development of novel computational techniques.Maintain and enhance the research lab's software projects, including websites, documentation, and code repositories.Troubleshoot scripts, manage deployments, and ensure the success of data-driven research projects.
This is a hybrid position which requires time onsite in Bethesda, MD.Key Responsibilities:
Develop, test, and refine novel programming methods, toolkits, and algorithms for bioinformatics and computational biology applications.Provide statistical modeling, server management, database management, and data visualization using tools like Python, R, Shiny, and MATLAB.Implement scientific applications to analyze complex datasets, including time series, genomics, and behavioral data.Design and optimize data processing pipelines for efficient data extraction, pre-processing, and visualization.Collaborate with researchers to apply computational techniques for biostatistics and statistical modeling across a variety of applications.Manage and maintain Linux-based (Debian) repositories and data storage systems for laboratory protocols and experimental data.Provide database support and maintenance to ensure data integrity, correction, and optimization using relational databases (PostgreSQL, MySQL).Develop and deploy dynamic web applications for bioinformatics, using modern technology stacks and cloud solutions.Qualifications:Education : Master's or Ph.D. in Computer Science, Data Science, Bioinformatics, Neuroscience, or a related field.Experience : Minimum 3 years of hands-on experience in data science, statistical modeling, machine learning, or bioinformatics.Programming Languages : Expertise in Python, R, Shiny, MATLAB, SQL, and GitHub.Data Science Tools : Proficiency with TensorFlow, PyTorch, scikit-learn, and XGBoost.Database Systems : Strong knowledge of PostgreSQL, MySQL, and experience with ETL processes and multivariate data extraction.Data Visualization : Experience with Tableau, Power BI, or other visualization platforms.Operating Systems : Proficient in Linux, especially Debian, for managing scientific data repositories.Machine Learning & AI : Applied experience with deep learning models, neural networks, and natural language processing (NLP).Collaborative Skills : Ability to work across teams to support research staff, troubleshoot technical issues, and provide bioinformatics solutions.Preferred Skills:Experience in developing scientific applications for bioinformatics research, including transcriptomics and genomics.Familiarity with cloud-based platforms like AWS or GCP for deploying machine learning models and managing large datasets.Experience working in a research environment, especially supporting data-driven biomedical research projects.Knowledge of high-performance computing (HPC) for bioinformatics data processing.Key Contributions:Create innovative AI and data science solutions to support bioinformatics research.Collaborate with researchers to solve complex scientific problems through the development of novel computational techniques.Maintain and enhance the research lab's software projects, including websites, documentation, and code repositories.Troubleshoot scripts, manage deployments, and ensure the success of data-driven research projects.