Data Science Neuroscience PhD Co-op

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world.  We provide an inclusive work environment where each person is considered as an individual.  At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Career Programs Job Sub Function: Non-LDP Intern/Co-Op Job Category: Career Program All Job Posting Locations: Cambridge, Massachusetts, United States of America Job Description: Johnson & Johnson Innovative Medicine is seeking a highly motivated PhD Co-op to join the Neuroscience DDSAI team for Spring 2027. This role offers a unique opportunity to work within the team building out a large single-cell and multi-omics atlas for neuropsychiatry.  The successful candidate will develop and apply advanced computational approaches to understand cell-type-specific disease mechanisms, map cell-cell communication networks, identify dysregulated signaling pathways in neuropsychiatry, and nominate novel therapeutic targets for neuropsychiatry discovery programs at J&J. In addition to cell-cell communication analyses, the candidate will explore cutting-edge AI/ML approaches that leverage large-scale single-cell, genetic, transcriptomic, proteomic, and multimodal datasets to systematically prioritize actionable therapeutic targets and pathways.

Cell-Cell Communication and Disease Biology Benchmark and apply state-of-the-art methods to map cell-cell communication networks in schizophrenia and bipolar disorder.  Identify disease-associated disruptions in ligand-receptor interactions and intercellular biological circuits across  cell populations.  Generate disease-specific cellular interaction maps to uncover novel mechanisms and target discovery opportunities in neuropsychiatric disorders. AI/ML-driven applications on single-cell atlases for target nomination Apply cutting-edge AI and single-cell analytics to uncover disease-associated cell states and pathways in schizophrenia and bipolar disorder. Leverage machine learning, network biology, and foundation models to identify novel therapeutic targets and disease mechanisms. Integrate single-cell discoveries with orthogonal multi-omics data to support precision target identification in neuropsychiatry. Drive translational impact through cross-functional collaboration Collaborate with multidisciplinary teams spanning Data Science, Precision Measures, and Neuropsychiatry Discovery to advance target discovery programs. Present findings to scientific leaders and contribute to publications, posters, and presentations at internal and external scientific conferences. Target Hire Date: 01/4/2027 Target End Date: 6/30/2027   Qualifications Required Currently pursuing a PhD in one of the following or a related quantitative discipline: Computational Biology, Bioinformatics, Systems Biology, Biomedical Sciences, Neuroscience, Computer Science, Data Science. Strong programming skills in Python and/or R (including effective use of AI-assisted coding). Experience analyzing high-dimensional multimodal biological datasets, with a preference for single-cell RNASeq, ATACSeq, proteomics, and genomics datasets. Familiarity with machine learning, statistics, and computational biology methods. Strong scientific communication and presentation skills. Preferred Experience with graph analytics, network biology,