Research areas include statistical/quantitative/population genetics, genealogical inference, machine learning, genetic prediction, genome-wide association studies, scalable linear mixed models, and efficient algorithms for large-scale genomic data analysis.

This is a one-year appointment starting as early as possible, with renewal possible based on the availability of funds, availability of work, and satisfactory performance.

• Develop novel statistical and computational methods for ARG-based quantitative genetics
• Analyze large-scale genetic and phenotypic datasets
• Implement scalable software and algorithms for genomic inference
• Collaborate with researchers across statistics, genetics, and computational biology
• Contribute to manuscripts, presentations, and open-source software development
• Participate in interdisciplinary collaborations related to predictive breeding and genome editing
• Travel to the United Kingdom to collaborate with project partners at the University of Edinburgh and the University of Oxford

• PhD in statistics, computer science, computational biology, genetics, applied mathematics, or a related quantitative field is required
• Proof of degree completion must be in hand on or before the start date
• Strong programming and computational skills
• Experience with statistical modeling, machine learning, or large-scale data analysis

• Experience with population genetics or statistical genetics
• Familiarity with Bayesian methods, probabilistic modeling, or graphical models
• Experience with scientific computing in Python, JAX, Torch, Julia, C++, or related languages
• Experience with high-performance computing or scalable algorithms
• Interest in interdisciplinary research spanning genomics and evolutionary biology

Salary and Benefits: Salary will be commensurate with experience and is expected to be in the range of $65,000 - $80,000 per year, plus benefits and a $3,000 relocation assistance bonus.

Research areas include statistical/quantitative/population genetics, genealogical inference, machine learning, genetic prediction, genome-wide association studies, scalable linear mixed models, and efficient algorithms for large-scale genomic data analysis.

This is a one-year appointment starting as early as possible, with renewal possible based on the availability of funds, availability of work, and satisfactory performance.

• Develop novel statistical and computational methods for ARG-based quantitative genetics
• Analyze large-scale genetic and phenotypic datasets
• Implement scalable software and algorithms for genomic inference
• Collaborate with researchers across statistics, genetics, and computational biology
• Contribute to manuscripts, presentations, and open-source software development
• Participate in interdisciplinary collaborations related to predictive breeding and genome editing
• Travel to the United Kingdom to collaborate with project partners at the University of Edinburgh and the University of Oxford

• PhD in statistics, computer science, computational biology, genetics, applied mathematics, or a related quantitative field is required
• Proof of degree completion must be in hand on or before the start date
• Strong programming and computational skills
• Experience with statistical modeling, machine learning, or large-scale data analysis

• Experience with population genetics or statistical genetics
• Familiarity with Bayesian methods, probabilistic modeling, or graphical models
• Experience with scientific computing in Python, JAX, Torch, Julia, C++, or related languages
• Experience with high-performance computing or scalable algorithms
• Interest in interdisciplinary research spanning genomics and evolutionary biology

Salary and Benefits: Salary will be commensurate with experience and is expected to be in the range of $65,000 - $80,000 per year, plus benefits and a $3,000 relocation assistance bonus.