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Postdoctoral Associate in Generative AI, Causal Inference, and Regulatory Genomics at Yale University, USA

Post-Doctoral Fellowship Position at USA, Ozbolat Laboratory at Penn State

Summary

The Department of Biostatistics at Yale University invites applications for a Postdoctoral Associate position in the Liu Lab. This exciting opportunity focuses on developing trustworthy AI systems that integrate Generative AI, Causal Inference, and Regulatory Genomics to uncover the molecular mechanisms underlying human diseases. The position offers access to world-class computational resources, interdisciplinary collaborations, and exceptional career development opportunities.

Postdoctoral Associate in Generative AI, Causal Inference, and Regulatory Genomics at Yale University, USA

Designation

Postdoctoral Associate

Research Area

  • Generative Artificial Intelligence (AI)
  • Causal Inference
  • Regulatory Genomics
  • Computational Biology
  • Statistical Genetics
  • Biostatistics
  • Deep Learning
  • Bayesian Generative Models
  • Foundation Models
  • Computational Genomics
  • Biomedical Data Science

Location

Department of Biostatistics, Yale University
New Haven, Connecticut, USA

Eligibility/Qualification

Applicants should:

  • Hold or expect to receive a Ph.D. in:
    • Computer Science
    • Computational Biology
    • Statistics
    • Biostatistics
    • Or a closely related discipline.
  • Have experience in one or more of the following:
    • Deep Learning
    • Generative Modeling
    • Causal Inference
    • Foundation Models
    • Computational Genomics
  • Possess strong programming skills in Python.
  • Be proficient with PyTorch or TensorFlow.
  • Have experience using Linux-based high-performance computing environments.
  • Demonstrate strong communication skills, creativity, and enthusiasm for interdisciplinary research.

Job Description

The selected Postdoctoral Associate will:

  • Lead research on developing trustworthy causal AI systems for biomedical discovery.
  • Build computational frameworks to identify causal genes, regulatory elements, and molecular pathways linking genotype to phenotype.
  • Analyze large-scale biomedical and genomic datasets using AI-powered statistical methods.
  • Collaborate closely with experts in biostatistics, genetics, and computational biology.
  • Utilize Yale’s advanced research computing infrastructure, including a large GPU cluster with over 250 GPUs.
  • Participate in interdisciplinary research spanning AI, statistics, genomics, and public health.
  • Receive mentorship in research, grant writing, scientific collaboration, and career development.

How to Apply

Interested candidates should submit:

  • Updated Curriculum Vitae (CV)
  • Cover Letter describing previous research experience and future research interests

Send application materials via email to:

Dr. Qiao Liu
Email: qiao.liu@yale.edu

Last Date for Apply

Not Specified (Applications will be reviewed until the position is filled. Early application is recommended.)

Link

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