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The University of Texas MD Anderson Cancer Center

Flatiron Research Fellow, Biological Transport Networks, Center for Computa

The University of Texas MD Anderson Cancer Center, New York, New York, us, 10261

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Flatiron Research Fellow, Biological Transport Networks, Center for Computational Biology Job Title: Flatiron Research Fellow, Biological Transport Networks, Center for Computational Biology Job Number: 107456 Location: New York, US

The Center for Computational Biology (CCB) of the Flatiron Institute is actively seeking enthusiastic, full‑time post‑doctoral researchers to join its Biological Transport Networks group in 2026. The primary objective of the group is to unravel the intricate relationships among the architecture of transport networks, their physical and developmental constraints, and their contribution to the overall fitness of the organisms they serve. By integrating computation, theory, and experimental data, we aim to bridge micro‑ and mesoscopic knowledge of living processes and the intricacies of large‑scale networks, ultimately unveiling biological principles that can provide insights into comparative physiology across species.

Responsibilities

Perform theoretical and computational research on biological transport networks.

Develop, implement, and maintain scientific software for large‑scale flow network simulations, machine learning, and topological data analysis.

Organize and participate in CCB and Flatiron Institute collaborative activities including seminars, workshops, and meetings.

Prepare manuscripts for publication and present research at scientific conferences.

Assist in student mentorship and provide training and guidance to CCB staff and visitors as needed.

Qualifications

Education : Ph.D. in applied mathematics, statistics, computational biology, biophysics, computer science, engineering, mathematical physics, or related disciplines.

Related Skills & Other Requirements :

Demonstrated abilities in mathematical modeling, analysis, scientific computation, scientific software and algorithm development, data analysis, inference, and image analysis.

Expertise in computational biology, modeling, machine learning, and scientific simulation.

Ability to work well in interdisciplinary environments and collaborate with experimentalists.

Strong oral and written communication, data documentation, and presentation skills.

Compensation and Benefits

Full‑time annual salary: $91,000.

Competitive benefits package provided by the Simons Foundation.

Application Instructions To apply, submit the following through the application portal: https://apptrkr.com/6615073.

Cover Letter

– summarize your most significant graduate‑school contributions.

Curriculum Vitae

with publication list and, if relevant, links to software.

Research Statement

(≤3 pages) describing past results, current and future interests, and potential synergies with CCB.

Letters of Recommendation

– at least two.

Applications for 2026 positions will be reviewed beginning November 2025 on a rolling basis until filled. Submissions are strongly encouraged by 2025‑11‑15.

Application Deadline 2025‑11‑15

Selection Criteria

Past research accomplishments.

Proposed research program.

Synergy with CCB staff and research programs and potential to cross boundaries with other Flatiron Institute centers.

Commitment to Expanding Pathways to Science & Opportunities for All Many of the greatest ideas and discoveries come from a diverse mix of minds, backgrounds, and experiences. The Simons Foundation is committed to advancing basic science and mathematics to benefit humankind and expand our collective understanding of our world. We support initiatives that broaden the scientific community and open pathways to science and mathematics careers.

Equal Opportunity Statement The Simons Foundation provides equal opportunities to all applicants without regard to race, religion, color, age, sex, pregnancy, national origin, sexual orientation, gender identity, genetic disposition, neurodiversity, disability, veteran status, or any other protected category under federal, state, and local law.

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