Post Doctoral Fellow

The Talent Acquisition department hires qualified candidates to fill positions which contribute to the overall strategic success of Howard University. Hiring staff “for fit” makes significant contributions to Howard University’s overall mission.

At Howard University, we prioritize well-being and professional growth.

Here is what we offer:

• Health & Wellness: Comprehensive medical, dental, and vision insurance, plus mental health support
• Work-Life Balance: PTO, paid holidays, flexible work arrangements
• Financial Wellness: Competitive salary, 403(b) with company match
• Professional Development: Ongoing training, tuition reimbursement, and career advancement paths
• Additional Perks: Wellness programs, commuter benefits, and a vibrant company culture

Join Howard University and thrive with us!

https://hr.howard.edu/benefits-wellness

JOB PURPOSE:

The Howard University Research Centers in Minority Institutions (RCMI) Program – Center for Computational Biology and Bioinformatics (CCBB) is seeking a highly motivated candidate for a Postdoctoral Research Fellowship position. In this role, the successful candidate will apply expertise in data science, machine learning, bioinformatics techniques as well as multi-omics integration to predict and validate clinical disease outcomes; work independently and develop research projects to identify patterns and insights from complex biological data of clinical outcomes; collaborate with RCMI investigators to develop and refine artificial intelligence/machine learning models to discover disease networks and biomarkers. Communicate research findings through peer-reviewed publications, internal and external presentations, and conferences.

SUPERVISORY AUTHORITY:

Responsible for orienting and training others and assigning and reviewing their work. May also be responsible for acting in a lead or senior capacity over other positions performing essentially the same work or related technical tasks and reporting to a higher level on a formal basis

NATURE AND SCOPE:

Internal contacts include administrators, faculty, staff and students both within the department and University-wide. External contacts include government agencies, sponsor representatives, vendors, visitors, officials and the general public.

PRINCIPAL ACCOUNTABILITIES:

• Plan, develop, execute, and coordinate strategies from complex biological data of clinical outcomes; and other types of projects as may be needed. Implement approved center/department policies and procedures in the pursuit/support of research projects and grant applications.
• Collaborate with RCMI investigators to develop and refine artificial intelligence/machine learning models to discover disease networks and biomarkers.
• Interact with peers to gain experience on ongoing project(s), report to PL concerning project execution, research operation and recommend operational changes, as needed.
• Prepare research manuscripts for publication, contribute to grant preparation, and contribute to preparation of annual reports.
• Ensure that research goals and objectives specified for the assigned project(s) are accomplished in accordance within established priorities, time and funding limitations, or other specifications.
• Develop and schedule project-specific research support plans in accordance with overall workload, project needs, and resources.
• Recommend additional equipment, software, and resources needed for project development.
• Prepare ad hoc reports on status of projects for the director/chair.
• Confer with and advise staff, students and faculty to provide technical advice, problem-solving assistance, and center/department policy information, answers to questions related to specific research projects.
• Work with evaluation professional(s) to advise and implement evaluation methodologies to assess center/department effectiveness.
• Perform other related duties as assigned.

CORE COMPETENCIES:

• Skilled in R, or Python and other programming languages for data analysis and statistical modeling.
• Experience with bioinformatics tools, large-scale datasets from public repositories, crucial for data analysis and research.
• Experience with machine learning algorithms, transformers, or large language models to analyze genomic data.
• Apply expertise in data science, and statistical learning approaches to identify patterns and predict clinical outcomes from complex biological data.
• Proficient in using Git/GitHub
• Excellent in manuscript writing and oral presentations, with the ability to convey complex information clearly.
• Able to identify opportunities, learn quickly, and apply innovative solutions.
• Strong team collaboration skills, and effective in multi-disciplinary environments.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills.

MINIMUM REQUIREMENTS:

Doctoral degree in quantitative discipline such as bioinformatics, computational biology, statistics, data science, computer science, software engineering, or related fields.

Compliance Salary Range Disclosure

$60,000

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