Hi all, I am currently on the academic job market. I am a postdoctoral researcher in Dr. Christina Leslie's lab at the Computational and Systems Biology Program at Memorial Sloan Kettering Cancer Center. My research focuses on deciphering causal and dynamic gene regulation mechanisms by integrating observational data—genomics, epigenomics, transcriptomics, and 3D chromatin conformation like Hi-C—with perturbational data from CRISPRi/a screens and Perturb-seq in single-cell multiomics. I employ techniques from statistical machine learning, causal inference, dynamical modeling, and artificial intelligence (AI) to achieve this goal. The models that I have developed include GraphReg, ENCODE-rE2G, and DynaVelo (to be submitted soon). Why is this important? Designing any effective and off-target-free therapeutic intervention for diseases, including cancer, first requires a complete understanding of the underlying wildtype system and then identifying the components that malfunction in disease states. With the ever-growing role of AI in synthetic biology and drug design, it is crucial to ensure that the models are causal and comprehend the basic biology of all cells. This is a challenging problem, but I am very hopeful that with the increasing scale of perturbational and multiomic data across cell types, we will achieve significant outcomes. If you believe I could be a good fit for your department, please reach out to me. Sincerely, Alireza