... bioinformatics pipelines for variant calling, structural variant detection, transcriptome profiling, and integrative multi-omics analyses. * Apply statistical and machine learning approaches to ...
... bioinformatics pipelines for variant calling, structural variant detection, transcriptome profiling, and integrative multi-omics analyses. * Apply statistical and machine learning approaches to ...
By leveraging Digital Pathology and employing AI and machine learning, they will optimize workflows ... and Bioinformatics to support our expanding clinical services, including integration of high ...
By leveraging Digital Pathology and employing AI and machine learning, they will optimize workflows ... and Bioinformatics to support our expanding clinical services, including integration of high ...
By leveraging Digital Pathology and employing AI and machine learning, they will optimize workflows ... and Bioinformatics to support our expanding clinical services, including integration of high ...
By leveraging Digital Pathology and employing AI and machine learning, they will optimize workflows ... and Bioinformatics to support our expanding clinical services, including integration of high ...
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 Alabama? The most popular types of Bioinformatics Machine Learning jobs in Alabama are:
What are popular job titles related to Freelance Bioinformatics Machine Learning jobs in Alabama? For Freelance Bioinformatics Machine Learning jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Freelance Bioinformatics Machine Learning jobs in Alabama look for? The top searched job categories for Freelance Bioinformatics Machine Learning jobs in Alabama are:
What cities in Alabama are hiring for Freelance Bioinformatics Machine Learning jobs? Cities in Alabama with the most Freelance Bioinformatics Machine Learning job openings:
Full-time
Re-posted 14 days ago
Job description
Position Details
To create a Posting, first complete the information on this screen, then click the Next button or select the page in the left hand navigation menu. Proceed through all sections completing all necessary information. To submit the Posting to Human Resources, you must go to the Posting Summary Page by clicking on the Next button until you reach the Posting Summary Page or select Posting Summary Page from the left navigation menu. Once a summary page appears, hover your mouse over the orange Action button for a list of possible approval step options.
Position Information
Position Title
Research Assistant Professor-Genomic Sequencing Data Analysis
Job Summary
We are seeking a highly skilled and motivated Research Assistant Professor with expertise in genomic sequencing data analysis to join our multidisciplinary research team. The successful candidate will lead computational and statistical analyses of large-scale genomic datasets, including whole-genome, whole-exome, and transcriptomic sequencing, to advance projects in cancer biology, precision medicine, and related biomedical fields. This position offers the opportunity to develop independent research while contributing to collaborative team science.
Essential Job Duties
Preferred Qualifications
Physical Demands
FLSA
Exempt
Status
Full-Time
Skills and Attributes
Posting Detail Information
Posting Number
Will this position required travel?
yes
Will this position required night, weekend, and after hour work?
yes
Will this positon be supported using grants or contract funding?
yes
Number of Vacancies
1
Desired Start Date
Position End Date (if temporary)
Open Date
04/07/2026
Close Date
Open Until Filled
No
Special Instructions Summary
Each applicant, including all current employees, must complete and submit the following documents:
Quick Link for Internal Postings
https://tuskegee.peopleadmin.com/postings/3659
To create a Posting, first complete the information on this screen, then click the Next button or select the page in the left hand navigation menu. Proceed through all sections completing all necessary information. To submit the Posting to Human Resources, you must go to the Posting Summary Page by clicking on the Next button until you reach the Posting Summary Page or select Posting Summary Page from the left navigation menu. Once a summary page appears, hover your mouse over the orange Action button for a list of possible approval step options.
Position Information
Position Title
Research Assistant Professor-Genomic Sequencing Data Analysis
Job Summary
We are seeking a highly skilled and motivated Research Assistant Professor with expertise in genomic sequencing data analysis to join our multidisciplinary research team. The successful candidate will lead computational and statistical analyses of large-scale genomic datasets, including whole-genome, whole-exome, and transcriptomic sequencing, to advance projects in cancer biology, precision medicine, and related biomedical fields. This position offers the opportunity to develop independent research while contributing to collaborative team science.
Essential Job Duties
- Perform high-quality computational analysis of next-generation sequencing (NGS) data, including short and long-read whole-genome, whole-exome, RNA-seq, and spatial transcriptomics datasets.
- Develop and implement bioinformatics pipelines for variant calling, structural variant detection, transcriptome profiling, and integrative multi-omics analyses.
- Apply statistical and machine learning approaches to identify genomic alterations, biomarkers, and functional networks.
- Collaborate with wet-lab scientists to integrate genomic data with experimental results.
- Contribute to manuscript preparation, figure generation, and presentation of findings at scientific conferences.
- Write and contribute to competitive grant applications, providing preliminary data and computational expertise.
- Mentor graduate students, postdoctoral fellows, and research staff in computational genomics.
- Maintain data management, quality control, and reproducibility standards in accordance with institutional and funding agency guidelines,
Preferred Qualifications
- Ph.D. or equivalent degree, with postdoctoral training in bioinformatics, computational biology, genomics, computer science, statistics, or related field.
- Demonstrated expertise in NGS data analysis, including quality control, alignment, variant calling, and downstream interpretation.
- Proficiency with bioinformatics tools (e.g., GATK, samtools, bcftools, STAR, HISAT2, Cell Ranger, Seurat) and programming languages (e.g., Python, R, Bash).
- Experience working with high-performance computing and cloud-based analysis platforms.
- Experience with cancer genomics, single-cell and spatial transcriptomics, or epigenomic data analysis.
Physical Demands
FLSA
Exempt
Status
Full-Time
Skills and Attributes
- Familiarity with database development, workflow management systems (e.g., Nextflow, Snakernake), and reproducible research practices (e.g., Docker, Git).
- Strong track record of peer-reviewed publications in genomic data analysis.
- Excellent problem-solving, organizational, and communication skills.
- Ability to work effectively in multidisciplinary research teams.
Posting Detail Information
Posting Number
Will this position required travel?
yes
Will this position required night, weekend, and after hour work?
yes
Will this positon be supported using grants or contract funding?
yes
Number of Vacancies
1
Desired Start Date
Position End Date (if temporary)
Open Date
04/07/2026
Close Date
Open Until Filled
No
Special Instructions Summary
Each applicant, including all current employees, must complete and submit the following documents:
- Tuskegee University employment application
- Cover Letter
- Resume/CV
- Recommendation letters
- Copies of unofficial transcripts.
- Please note that official transcripts(s) will be required upon hire
Quick Link for Internal Postings
https://tuskegee.peopleadmin.com/postings/3659
About Tuskegee University
Sourced by ZipRecruiter
Industry
Colleges, universities, and professional schools
Company size
1,001 - 5,000 Employees
Headquarters location
Tuskegee, AL, US
Year founded
1881