Variant calling and basic annotation and DNA methylation data processing and analysis and Data ... law. This position is contingent upon contract award.
Variant calling and basic annotation and DNA methylation data processing and analysis and Data ... law. This position is contingent upon contract award.
Postdoctoral Fellow
Baltimore, MD · On-site
$48K - $66K/yr
Possess a working knowledge in genomic sciences (i.e., genome sequencing and data analysis) and ... annotation of metagenomes) * Lead or participate in writing research and review papers, and to ...
Postdoctoral Fellow
Baltimore, MD · On-site
$48K - $66K/yr
Possess a working knowledge in genomic sciences (i.e., genome sequencing and data analysis) and ... annotation of metagenomes) * Lead or participate in writing research and review papers, and to ...
Data Annotation Law information
What are the key skills and qualifications needed to thrive as a data annotation specialist?
To thrive as a Data Annotation Specialist, you need keen attention to detail, strong analytical skills, and a basic understanding of data labeling protocols, often supported by a high school diploma or relevant training. Familiarity with data annotation tools like Labelbox, Supervisely, or CVAT, as well as knowledge of data privacy regulations, is typically required. Excellent communication, time management, and consistency are vital soft skills for collaborating with teams and maintaining annotation quality. These skills ensure accurate, reliable data labeling, which is critical for developing effective machine learning models.
What is the difference between Data Annotation Law vs Data Labeler?
| Aspect | Data Annotation Law | Data Labeler |
|---|---|---|
| Credentials | Legal knowledge, compliance certifications | Basic training, attention to detail |
| Work Environment | Legal offices, compliance departments | Data annotation platforms, remote or office settings |
| Industry Usage | Legal, AI compliance, data privacy | AI training, machine learning datasets |
| Search & Comparison | Legal roles, compliance in data annotation | Data labeling, data annotation jobs |
Data Annotation Law involves legal expertise ensuring data annotation processes comply with laws and regulations, often requiring legal certifications. Data Labelers focus on annotating data for AI models, typically with basic training. While both roles work within data annotation, Data Annotation Law emphasizes legal compliance, whereas Data Labelers concentrate on data preparation for machine learning.
What is data annotation law?
Data Annotation Law refers to the legal frameworks and regulations that govern the process of labeling, tagging, or categorizing data for use in machine learning and artificial intelligence applications. These laws address issues such as data privacy, intellectual property, consent, and the ethical use of annotated data. Data Annotation Law ensures that organizations handle data responsibly and comply with national and international standards when using human annotators or automated systems. It is crucial for companies to understand these legal requirements to avoid potential legal liabilities and protect the rights of data subjects.
What are some common challenges faced by professionals working in data annotation for the legal industry, and how can they be addressed?
Professionals in data annotation law often encounter challenges such as interpreting complex legal language, ensuring consistency and accuracy in labeling, and maintaining confidentiality with sensitive information. Collaboration with legal experts and ongoing training in legal terminology are essential to address these issues. Additionally, many organizations implement rigorous quality assurance processes and utilize annotation guidelines to help annotators navigate ambiguous cases and improve overall data quality.
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Job description
Position Objective: The National Institutes of Health requires contractor support for laboratory and computational analysis of genomic and epigenomic data. The work supports ongoing research involving genotyping, long-range sequencing, and DNA methylation profiling at the National Institute on Aging (NIA) within the National Institutes of Health (NIH).
Duties and Responsibilities:
- Evaluate: Read quality, coverage, and depth and Sample integrity and contamination
- Flag anomalies and provide preliminary interpretation.
- Perform DNA extraction from blood, tissue, or cultured cells using established protocols. 1
- Conduct genotyping assays (e.g., SNP arrays, PCR-based methods 2
- Support long-range sequencing workflows (e.g., library prep and sequencing using long-read platforms such as PacBio or Oxford Nanopore). 3
- Perform DNA methylation assays (e.g., bisulfite conversion, array-based or sequencing-based methods).
- Execute established QC pipelines for sequencing and genotyping data.
- Compile and document QC metrics in standardized formats.
- Modify existing scripts and pipelines to support project needs.
- Perform data analysis using: R (statistical analysis and visualization) and Scripting (Python, Bash, or equivalent)
- Conduct: Variant calling and basic annotation and DNA methylation data processing and analysis and Data integration across datasets when directed
- Maintain accurate laboratory notebooks and electronic records.
- Identify routine technical issues and implement standard troubleshooting steps.
- Prepare: Summary tables and figures and Written summaries of methods and results
- Present findings in internal meetings to NIH staff
- Contribute to draft reports, manuscripts, or project updates.
- Sample Processing Logs DNA extraction records and yields
- Genotyping/Sequencing Outputs Raw and processed data files
- QC Reports Standardized quality metrics and summaries
- Analysis Outputs Variant and methylation results, visualizations
- Scripts and Code Documented R/Python/Bash scripts
- Monthly Summary of work performed and findings
- Presentation Materials Slides or briefings for NIH staff
Basic Qualifications:
- Masters Degree in Biology or similar field of study
- At least 2 years of experience
- Proficiency in R and at least one scripting language
- Experience with QC and data visualization
- Familiarity with genomic data formats (FASTQ, BAM, VCF)
Minimum Qualifications:
- Strong communication skills, both oral and written.
- Detail-oriented and possess strong organizational skills with the ability to prioritize multiple tasks and projects.
*This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required by this position.
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed above are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
GAP Solutions provides reasonable accommodations to qualified individuals with disabilities. If you need an accommodation to apply for a job us at recruiting@gapsi.com. You will need to reference the requisition number of the position in which you are interested. Your message will be routed to the appropriate recruiter who will assist you. Please note, this email address is only to be used for those individuals who need an accommodation to apply for a job. Emails for any other reason or those that do not include a requisition number will not be returned.
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law.
This position is contingent upon contract award.