Job Description
We are seeking a highly motivated postdoctoral researcher to join the Zero Knowledge Discovery Lab ( to work on problems at the intersection of biology, medicine, mathematics and computation. The successful candidate will contribute to the development of next-generation learning algorithms to understand human health trajectories through advanced digital twin frameworks, ranging from analyzing the darkome of genomic data to developing digital twins for the human microbiome/metabolome. One of our funded projects that the candidate will work on is MAGICS: Methodological Advancements for Generalizable Insights into Complex Systems funded by DARPA (
The ideal candidate will be an applied mathematician with equally sophisticated skillsets in theorem proving, algorithms and coding.
Requirements:
- PhD in computer science, physics, engineering, statistics or applied mathematics is required.
- A strong foundation in mathematical modeling. Familiarity with stochastic processes, information theory and discrete mathematics is a plus.
- Programming Skills: Proficiency in Python, familiarity with scikit-learn is good, experience in C++ is a plus
- Documented Productivity: Record of peer-reviewed publications
- Interdisciplinary Interest: Candidates should have a passion for applying computational techniques to solve complex problems across disciplines.
Key Responsibilities:
- Mathematical Foundations: Work on the rigorous mathematical foundations of emerging digital twin frameworks, and the theoretical aspects of ML. Example papers: ,
- Research & Algorithm Development: Develop advanced algorithms to predict complex health trajectories, simulating individual patient journeys, and providing real-time dynamic views of patient health. This involves working with multimodal datasets, including EHRs, genetic data, and social determinants of health.
- Collaborative Research: Engage with a diverse group of researchers in fields such as computational biology, medicine, and social sciences. Publish findings in top-tier journals, present at conferences, and contribute to the advancement of the field.
Compensation and Benefits:
- Competitive Salary: Funding is available for a competitive salary, based on qualifications and experience.
- Research Support: Additional funding will be provided for supplies and travel to conferences.
- Professional Development: Opportunities for significant career growth, networking with leading researchers, and engaging in high-impact interdisciplinary projects.
- Women and underrepresented groups are encouraged to apply.
Please contact Dr. Ishanu Chattopadhyay (ishanu_ch@uky.edu) for application details with CV and github link if available
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