gene network PostDoc positions and fellowships

A three-year PhD position at ENS Lyon studying how environmental dynamics influences the evolution of adaptive strategies in biological systems, particularly focusing on the evolution of stochastic phenotypic variation and regulated phenotypic variation in yeast.

The PhD candidate will join the Multiscale Physics of Morphogenesis team led by Hervé Turlier at the Centre for Integrative Biology of Toulouse, CNRS UMR5077 / University of Toulouse. The project combines physical modeling of tissues, multi-agent reinforcement learning, and information theory to understand how local cellular decisions based on internal state, neighborhood signaling, and tissue mechanics give rise to robust embryonic forms. Using agents representing cells that sense local information and adapt behaviors such as division, polarity, adhesion, tension, or signaling, the research aims to uncover rules that generate reproducible morphogenetic trajectories. The work will draw on mechanochemical models and data from embryonic systems such as the invariant ascidian and the more variable mouse embryo, seeking to develop a general computational framework for studying the emergence of form from gene‑mechanic‑signaling‑cellular interactions.

The University of Murcia invites applications for a postdoctoral researcher position focused on research into next-generation networks. The role is part of the 'Research into next-generation networks' line, aiming to investigate emerging technologies and architectures for future communication systems. Candidates must hold a PhD or equivalent and meet the Recognised Researcher (R2) profile. The position is full-time, based in Murcia, Spain, with an application deadline of 24 June 2026.

The Department of Animal and Veterinary Sciences at Aarhus University invites applications for a two-year postdoctoral position in Bioinformatics and Genomic Epidemiology. The successful candidate will contribute to two EU Partnership-funded projects focusing on animal health, antimicrobial resistance, and disease surveillance using multi-omics data, including whole-genome and metagenomic sequences. Responsibilities include developing bioinformatics pipelines, applying AI and machine learning methods for genome-to-phenome analysis, participating in international consortia meetings, and supporting teaching and supervision of graduate students. The position offers a collaborative research environment, access to high-performance computing facilities, and opportunities for professional development within a leading veterinary science department.

This PhD project focuses on developing process analytical technologies (PAT) for monitoring Adeno-associated virus (AAV) production during cell culture. The research aims to address manufacturing challenges in producing viral vectors for gene therapies through a collaborative program involving NIBRT, UCD, and an industrial partner in Dublin, Ireland.

This postdoctoral fellowship in the Department of Pathology at the University of Maryland School of Medicine invites candidates to work on histidine‑rich carriers delivering doxorubicin siRNA and tumor‑suppressor plasmids to combat breast cancer. The role involves designing, testing, and optimizing non‑viral gene‑delivery systems in mouse models, requiring a Ph.D. or M.D./Ph.D. and preferably experience in pharmacology, chemistry, molecular biology, and animal handling.

This PhD position focuses on developing an interpretable and thermodynamically consistent generative AI model for active mechanical metamaterials using Kolmogorov-Arnold networks. The research aims to integrate thermodynamic principles into machine learning frameworks to improve the design and understanding of programmable materials that respond to external stimuli.

Postdoctoral position in Dr. Chen Kam's laboratory at UCLA's Division of Dermatology, focusing on understanding vascular network development and regeneration using non-invasive live imaging techniques. Requires M.D., Ph.D., or M.D./Ph.D. with background in vascular biology or related fields.