This position is an outstanding opportunity for a computational scientist with strong training in bioinformatics, machine learning, and large-scale genomic data analysis to work at the interface of ...
This position is an outstanding opportunity for a computational scientist with strong training in bioinformatics, machine learning, and large-scale genomic data analysis to work at the interface of ...
Bioinformaticist
Charlottesville, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist
Charlottesville, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist
Reston, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist
Reston, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist
Charlottesville, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist
Charlottesville, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist
Charlottesville, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist
Charlottesville, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist with Security Clearance
Charlottesville, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
Bioinformaticist with Security Clearance
Charlottesville, VA · On-site
$99K - $225K/yr
... machine learning techniques, including classification or regression models, clustering algorithms, and graph-based approaches for biological data * Experience with bioinformatics visualization tools ...
... machine learning, multiple clouds) serve more users than almost any other US Government Agency ... Practical knowledge of bioinformatics, bioinformatic tools, and the application of genomic ...
... machine learning, multiple clouds) serve more users than almost any other US Government Agency ... Practical knowledge of bioinformatics, bioinformatic tools, and the application of genomic ...
... machine learning, multiple clouds) serve more users than almost any other US Government Agency ... Practical knowledge of bioinformatics, bioinformatic tools, and the application of genomic ...
... machine learning, multiple clouds) serve more users than almost any other US Government Agency ... Practical knowledge of bioinformatics, bioinformatic tools, and the application of genomic ...
... bioinformatics and computational biology. The lab's research program focuses on developing ... Current ongoing projects include: statistical modeling and advanced machine learning/AI method ...
... bioinformatics and computational biology. The lab's research program focuses on developing ... Current ongoing projects include: statistical modeling and advanced machine learning/AI method ...
... bioinformatics, computational biology, or a closely related field * Demonstrated experience using long- or short-read RNA-seq to understand alternative splicing * Experience using machine learning ...
... bioinformatics, computational biology, or a closely related field * Demonstrated experience using long- or short-read RNA-seq to understand alternative splicing * Experience using machine learning ...
... bioinformatics, web science, survey data science to scientific machine learning, explainable AI and generative AI. Faculty of the School of Data Science actively collaborate with researchers from ...
... bioinformatics, web science, survey data science to scientific machine learning, explainable AI and generative AI. Faculty of the School of Data Science actively collaborate with researchers from ...
This position will focus on developing and applying novel statistical methods, machine learning ... Doctoral degree in Biostatistics, Statistics, Computer Science, Data Science, Bioinformatics, or a ...
This position will focus on developing and applying novel statistical methods, machine learning ... Doctoral degree in Biostatistics, Statistics, Computer Science, Data Science, Bioinformatics, or a ...
Postdoctoral Associate
Blacksburg, VA · On-site
... Machine Learning (SciML). They will be expected to collaborate with members of the group as well as ... Biology, Bioinformatics, Statistics, Mathematics, Biophysics, Physics, Chemistry, Biology or ...
Postdoctoral Associate
Blacksburg, VA · On-site
... Machine Learning (SciML). They will be expected to collaborate with members of the group as well as ... Biology, Bioinformatics, Statistics, Mathematics, Biophysics, Physics, Chemistry, Biology or ...
Postdoctoral Associate
Blacksburg, VA · On-site
$63K - $73K/yr
... Machine Learning (SciML). They will be expected to collaborate with members of the group as well as ... Biology, Bioinformatics, Statistics, Mathematics, Biophysics, Physics, Chemistry, Biology or ...
Postdoctoral Associate
Blacksburg, VA · On-site
$63K - $73K/yr
... Machine Learning (SciML). They will be expected to collaborate with members of the group as well as ... Biology, Bioinformatics, Statistics, Mathematics, Biophysics, Physics, Chemistry, Biology or ...
Proficiency with bioinformatics tools and sequence analysis * Knowledge of biosafety/biosecurity ... Experience with HPC, GIS, machine learning, uncertainty quantification Chemical Defense Analyst ...
Proficiency with bioinformatics tools and sequence analysis * Knowledge of biosafety/biosecurity ... Experience with HPC, GIS, machine learning, uncertainty quantification Chemical Defense Analyst ...
Proficiency with bioinformatics tools and sequence analysis * Knowledge of biosafety/biosecurity ... Experience with HPC, GIS, machine learning, uncertainty quantification Chemical Defense Analyst ...
Proficiency with bioinformatics tools and sequence analysis * Knowledge of biosafety/biosecurity ... Experience with HPC, GIS, machine learning, uncertainty quantification Chemical Defense Analyst ...
Senior Associate HPC AI Scientist
$145K - $165K/yr
... AI and machine learning initiatives within a large-scale highperformance computing (HPC ... Biology, Bioinformatics, or a related discipline * Strong handson experience developing and ...
Senior Associate HPC AI Scientist
$145K - $165K/yr
... AI and machine learning initiatives within a large-scale highperformance computing (HPC ... Biology, Bioinformatics, or a related discipline * Strong handson experience developing and ...
Senior Associate HPC AI Scientist
Arlington, VA · On-site
$145K - $165K/yr
... AI and machine learning initiatives within a large-scale high-performance computing (HPC ... Biology, Bioinformatics, or a related discipline * Strong hands-on experience developing and ...
Senior Associate HPC AI Scientist
Arlington, VA · On-site
$145K - $165K/yr
... AI and machine learning initiatives within a large-scale high-performance computing (HPC ... Biology, Bioinformatics, or a related discipline * Strong hands-on experience developing and ...
... machine learning and data mining, artificial intelligence, robotics, visual computing, theory, databases, bioinformatics, HCI, and software engineering. The department has grown from 550 ...
... machine learning and data mining, artificial intelligence, robotics, visual computing, theory, databases, bioinformatics, HCI, and software engineering. The department has grown from 550 ...
Freelance Bioinformatics Machine Learning information
What does a Freelance Bioinformatics Machine Learning specialist do?
A Freelance Bioinformatics Machine Learning specialist applies machine learning techniques to analyze biological data, such as genomics, proteomics, and medical records, on a project-by-project basis. They typically work independently with research labs, biotech companies, or healthcare organizations to develop algorithms, build predictive models, and interpret complex biological datasets. Their work helps drive insights in areas like drug discovery, personalized medicine, and disease prediction, often leveraging tools like Python, R, and specialized bioinformatics software. As freelancers, they have the flexibility to choose projects, set their schedules, and work remotely.
What are the key skills and qualifications needed to thrive as a Freelance Bioinformatics Machine Learning Specialist, and why are they important?
To thrive as a Freelance Bioinformatics Machine Learning Specialist, you need a strong background in biology, statistics, and programming (such as Python or R), typically supported by a relevant degree in bioinformatics, computer science, or a related field. Familiarity with bioinformatics tools (e.g., BLAST, Bioconductor), machine learning libraries (scikit-learn, TensorFlow), and experience with cloud computing platforms are highly valuable. Strong problem-solving, communication, and project management skills help distinguish top freelancers in this field. These capabilities are crucial for independently delivering accurate, actionable biological insights to clients and efficiently managing multiple projects.
What are some common challenges freelance bioinformatics machine learning professionals face when working with multiple clients?
Freelance bioinformatics machine learning professionals often encounter challenges such as managing diverse data formats, aligning project expectations, and ensuring data privacy across multiple clients. Each client may have unique datasets, varying levels of documentation, and different computational infrastructure, requiring adaptability and strong communication skills. Balancing multiple deadlines and maintaining clear, consistent reporting are also important to foster trust and long-term collaborations.
What is the difference between Freelance Bioinformatics Machine Learning vs Freelance Data Scientist?
| Aspect | Freelance Bioinformatics Machine Learning | Freelance Data Scientist |
|---|---|---|
| Credentials | Background in bioinformatics, biology, or related fields; knowledge of machine learning | Background in statistics, computer science, or related fields; strong programming skills |
| Work Environment | Research labs, biotech companies, academic projects, freelance consulting | Various industries including finance, tech, healthcare, consulting |
| Industry Usage | Primarily biotech, healthcare, genomics, pharmaceutical sectors | Broad industry application including finance, marketing, tech, healthcare |
Freelance Bioinformatics Machine Learning specialists focus on applying machine learning techniques to biological data, often working within biotech and healthcare sectors. In contrast, Freelance Data Scientists have a broader scope, working across multiple industries with diverse datasets. Both roles require strong analytical skills and programming expertise, but their industry focus and domain knowledge differ significantly.
What are the most commonly searched types of Bioinformatics Machine Learning jobs in Virginia? The most popular types of Bioinformatics Machine Learning jobs in Virginia are:
What are popular job titles related to Freelance Bioinformatics Machine Learning jobs in Virginia? For Freelance Bioinformatics Machine Learning jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Freelance Bioinformatics Machine Learning jobs in Virginia look for? The top searched job categories for Freelance Bioinformatics Machine Learning jobs in Virginia are:
What cities in Virginia are hiring for Freelance Bioinformatics Machine Learning jobs? Cities in Virginia with the most Freelance Bioinformatics Machine Learning job openings:
Full-time
Posted 8 days ago
University Of Virginia rating
7.8
Based on 34 frontline employees who took The Breakroom Quiz
198th of 541 rated colleges and universities
Job description
scholarship during the training period.
The Department of Genome Sciences at the University of Virginia is seeking a highly motivated Postdoctoral Research Associate to join the Miller Lab and contribute to the Leducq COMET Network, an international collaborative effort focused on understanding the mechanisms of vascular calcification and related cardiovascular diseases.
This position is an outstanding opportunity for a computational scientist with strong training in bioinformatics, machine learning, and large-scale genomic data analysis to work at the interface of human genetics, single-cell and spatial multi-omics, cardiovascular biology, and translational medicine. The successful candidate will develop and apply advanced computational approaches to identify disease-associated genes, pathways, cell states, and regulatory mechanisms involved in vascular calcification, atherosclerosis, and broader cardiovascular disease.
Founded in 1819 by Thomas Jefferson, the University of Virginia is renowned for its commitment to advancing knowledge, educating leaders, and cultivating informed citizenship. The Department of Genome Sciences addresses fundamental questions in biology, public health, and medicine by developing and applying state-of-the-art genetic, genomic, computational, and multi-omic approaches to complex human diseases. The Miller Lab focuses on unraveling cardiovascular disease mechanisms by integrating large-scale human genetics, single-cell and spatial multi-omics, functional genomics, and data science approaches.
As part of the Leducq COMET Network, the successful candidate will work in a highly collaborative international environment involving data scientists, genomicists, statisticians, vascular biologists, cardiologists, and other clinical and translational experts. The candidate will contribute to the development of scalable computational pipelines, machine learning workflows, and integrative analyses that enable mechanistic discovery across diverse genomic and multi-omic datasets.
The successful candidate will be expected to:
Required qualifications:
Preferred qualifications:
Ideal candidate profile:
The ideal candidate will be a rigorous and creative computational scientist who enjoys developing new analytical approaches while working closely with experimental, clinical, and quantitative collaborators. They will have a strong track record of programming, data
analysis, and problem-solving, along with the ability to communicate complex computational results clearly to both technical and non-technical audiences. A strong team-oriented mindset and enthusiasm for mentoring junior researchers are essential.
This is a restricted position, which is dependent on funding and is contingent upon funding availability. This is a 12-month appointment with the possibility of renewal contingent upon satisfactory performance and the availability of funding.
This position is based in Charlottesville, VA, and must be performed fully on-site.
Salary range : 50-70k yearly will be commensurate with education and experience
How to Apply
Please apply online, by searching for requisition number R0083987. Complete an application with the following documents:
Upload all materials into the resume submission field. You can submit multiple documents into this one field or combine them into one PDF. Applications without all required documents will not receive full consideration.
Internal applicants: Search and apply for jobs on the UVA Internal Careers website.
The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA's commitment to non-discrimination and equal opportunity employment .
The Department of Genome Sciences at the University of Virginia is seeking a highly motivated Postdoctoral Research Associate to join the Miller Lab and contribute to the Leducq COMET Network, an international collaborative effort focused on understanding the mechanisms of vascular calcification and related cardiovascular diseases.
This position is an outstanding opportunity for a computational scientist with strong training in bioinformatics, machine learning, and large-scale genomic data analysis to work at the interface of human genetics, single-cell and spatial multi-omics, cardiovascular biology, and translational medicine. The successful candidate will develop and apply advanced computational approaches to identify disease-associated genes, pathways, cell states, and regulatory mechanisms involved in vascular calcification, atherosclerosis, and broader cardiovascular disease.
Founded in 1819 by Thomas Jefferson, the University of Virginia is renowned for its commitment to advancing knowledge, educating leaders, and cultivating informed citizenship. The Department of Genome Sciences addresses fundamental questions in biology, public health, and medicine by developing and applying state-of-the-art genetic, genomic, computational, and multi-omic approaches to complex human diseases. The Miller Lab focuses on unraveling cardiovascular disease mechanisms by integrating large-scale human genetics, single-cell and spatial multi-omics, functional genomics, and data science approaches.
As part of the Leducq COMET Network, the successful candidate will work in a highly collaborative international environment involving data scientists, genomicists, statisticians, vascular biologists, cardiologists, and other clinical and translational experts. The candidate will contribute to the development of scalable computational pipelines, machine learning workflows, and integrative analyses that enable mechanistic discovery across diverse genomic and multi-omic datasets.
The successful candidate will be expected to:
- Develop and apply computational methods for the analysis of large-scale genomic, epigenomic, transcriptomic, single-cell, spatial, and multi-omic datasets relevant to vascular calcification and cardiovascular disease.
- Build, benchmark, and maintain robust bioinformatics pipelines for data processing, quality control, integration, visualization, and reproducible analysis.
- Use machine learning and statistical approaches to identify disease-associated genes, pathways, regulatory programs, cell states, and molecular mechanisms.
- Integrate human genetics, functional genomics, and multi-omic datasets to prioritize candidate genes and causal pathways involved in vascular calcification and cardiovascular disease.
- Work closely with lab members and Leducq COMET Network collaborators to harmonize datasets, refine analysis strategies, and interpret findings in a biological and clinical context.
- Present progress in weekly group meetings and monthly consortium meetings.
- Draft manuscripts, contribute to grant applications, and support dissemination of findings through publications and presentations at national and international conferences.
- Contribute to the training and mentorship of junior lab members, including graduate students, undergraduate researchers, and computational trainees.
Required qualifications:
- PhD degree in bioinformatics, computational biology, genomics, genetics, biostatistics, statistics, computer science, biomedical engineering, systems biology, or a related quantitative discipline.
- Strong programming skills in R and Python.
- Experience working in Linux/Unix environments and using bash, high-performance computing systems, and reproducible computational workflows.
- Experience analyzing large-scale genomic or multi-omic datasets.
- Familiarity with workflow management systems such as Nextflow.
- Strong understanding of statistical analysis, data visualization, and reproducible research practices.
- Excellent written and oral communication skills.
- Demonstrated ability to work both independently and as part of a collaborative, cross-functional team.
Preferred qualifications:
- Experience with single-cell RNA-seq, single-cell ATAC-seq, spatial transcriptomics, epigenomics, proteomics, or other high-dimensional omics datasets.
- Familiarity with cardiovascular biology, vascular disease, vascular calcification, atherosclerosis, or related disease areas.
- Experience with machine learning frameworks and workflows, including PyTorch, scikit-learn, and standard supervised and unsupervised learning approaches.
- Experience developing, containerizing, and documenting reusable computational pipelines.
- Familiarity with version control, package development, cloud or HPC deployment, and collaborative coding practices.
- Prior experience contributing to manuscripts, grants, consortium projects, or large collaborative research efforts.
Ideal candidate profile:
The ideal candidate will be a rigorous and creative computational scientist who enjoys developing new analytical approaches while working closely with experimental, clinical, and quantitative collaborators. They will have a strong track record of programming, data
analysis, and problem-solving, along with the ability to communicate complex computational results clearly to both technical and non-technical audiences. A strong team-oriented mindset and enthusiasm for mentoring junior researchers are essential.
This is a restricted position, which is dependent on funding and is contingent upon funding availability. This is a 12-month appointment with the possibility of renewal contingent upon satisfactory performance and the availability of funding.
This position is based in Charlottesville, VA, and must be performed fully on-site.
Salary range : 50-70k yearly will be commensurate with education and experience
How to Apply
Please apply online, by searching for requisition number R0083987. Complete an application with the following documents:
- CV (required)
- Cover letter (required)
- Academic transcripts (optional)
- Names of 3 references (required)
Upload all materials into the resume submission field. You can submit multiple documents into this one field or combine them into one PDF. Applications without all required documents will not receive full consideration.
Internal applicants: Search and apply for jobs on the UVA Internal Careers website.
The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA's commitment to non-discrimination and equal opportunity employment .
What University Of Virginia employees say
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Benefits
Hours and flexibility
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About University of Virginia
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The University of Virginia is distinctive among institutions of higher education. Founded by Thomas Jefferson in 1819, the University sustains the ideal of developing, through education, leaders who are well-prepared to shape the future of the nation.
Industry
Colleges, universities, and professional schools
Company size
10,000+ Employees
Headquarters location
Charlottesville, VA, US
Year founded
1819