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Genomics Phd Jobs (NOW HIRING)

OU Health

Pathology PhD - PRN

Oklahoma City, OK

Pathology PhD - PRN Department: Ctyo-Genetics & BioChem Lab This is a full-time position in the OU ... Genomics) Current OU Health Employees - Please click HERE to login. OU Health is an equal ...

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Genomics Phd information

What is the difference between Genomics Phd vs Bioinformatics Scientist?

AspectGenomics PhdBioinformatics Scientist
Required CredentialsPhD in Genomics, Genetics, or related fieldBachelor's or Master's in Bioinformatics, Computer Science, or related field; PhD preferred
Work EnvironmentResearch labs, academic institutions, biotech companiesResearch institutions, biotech, pharmaceutical companies, tech firms
Industry UsageDesigns experiments, analyzes genomic data, publishes researchDevelops algorithms, analyzes large datasets, supports research projects

While both roles involve genomic data analysis, a Genomics Phd typically focuses on experimental design and research in genomics, whereas a Bioinformatics Scientist emphasizes computational analysis and algorithm development. Both careers require strong analytical skills, but the Genomics Phd is more research-oriented, often leading to academic or research positions, while Bioinformatics Scientists are more involved in data processing within industry settings.

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Postdoctoral Fellow in Bioinformatics - Chemoproteomics & Cancer Functional Genomics

Postdoctoral Fellow in Bioinformatics - Chemoproteomics & Cancer Functional Genomics

H. Lee Moffitt Cancer Center

Tampa, FL • On-site

$28.50 - $34.21/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Moffitt Cancer Center rating

8.1

Company rating: 8.1 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

70th of 870 rated healthcare providers

Job description

Postdoctoral Fellow in Bioinformatics - Chemoproteomics & Cancer Functional Genomics
Position Overview
A postdoctoral fellow position is available for a highly motivated scientist with expertise in bioinformatics, chemoproteomics, and functional genomics. The successful candidate will participate in research projects leveraging large-scale chemoproteomics datasets, integrating these with public cancer genomics resources, and mining CRISPR screening data to advance cancer biology and therapeutic discovery.
Key Responsibilities:
  • Analyze and integrate high-dimensional chemoproteomics datasets with multi-omotic data (e.g., genomics, transcriptomics, proteomics) from public repositories such as DepMap and TCGA
  • Develop, implement, and maintain robust computational pipelines in R and other programming languages (e.g., Python) for data processing, statistical analysis, and visualization
  • Mine and interpret large-scale CRISPR screening datasets to identify novel cancer dependencies and therapeutic targets, utilizing resources such as DepMap and published CRISPR screens
  • Collaborate with interdisciplinary teams of biologists, chemists, and clinicians to design and execute integrative studies, and contribute to the functional validation of computational predictions
  • Present research findings at internal meetings and national/international conferences; publish results in high-impact journals
  • Mentor junior researchers and contribute to grant writing and manuscript preparation

Required Qualifications:
  • PhD in Bioinformatics, Computational Biology, Cancer Biology, Genomics, or a related field is required
  • Demonstrated expertise in R and proficiency in other programming languages (e.g., Python)
  • Experience working with and mining large public cancer genomics databases, such as DepMap and TCGA
  • Proven track record in analyzing and integrating chemoproteomics and/or functional genomics datasets, especially CRISPR screening data
  • Strong understanding of statistics and machine learning concepts as applied to biological data
  • Excellent written and verbal communication skills, with a history of publishing in peer-reviewed journals
  • Ability to work independently and collaboratively in a multidisciplinary research environment

Preferred Qualifications
• Experience with drug development and/or chemistry
• Familiarity with AI/ML approaches for biological data analysis.
• Prior experience in cancer research or translational bioinformatics
Application Instructions:
Interested applicants should submit a CV, a cover letter outlining research experience and interests, and contact information for three references. Applications will be reviewed on a rolling basis.

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