div class="posting-requirements plain-list">PhD in Bioinformatics, Computational Biology, or related quantitative field (or MS with 5+ years relevant industry experience);
Demonstrated track record applying computational TF ranking and GRN inference to cellular reprogramming problems, transdifferentiation, directed differentiation, or iPSC systems;
Multi-platform single-cell RNA-seq expertise: hands-on analysis from at least two different platforms, including platform-specific troubleshooting and quality control;
Multi-modal genomics proficiency: ChIP-seq, CUT&RUN, or ATAC-seq analysis including peak calling, differential accessibility, and TF motif enrichment;
Hands-on experience with established GRN inference methods to nominate or rank regulators of cell state, beyond literature-curated lists;
Experience analyzing pooled perturbation screens (CRISPRa, CRISPR knockout, or barcoded TF overexpression) with single-cell or bulk readouts;
Working knowledge of trajectory inference and pseudotime methods for mapping cell state transitions;
Strong programming skills in Python and R, with proficiency in Scanpy/Seurat and statistical analysis for high-dimensional data;
Comfortable working in a modern computational environment: cloud platforms, workflow managers, containerization, and collaborative version control;
Strong publication record and demonstrated cross-functional collaboration with experimental biologists.
Lead end-to-end TF discovery for cellular reprogramming - from multi-platform single-cell genomics analysis (scRNA-seq, ATAC-seq) through GRN inference, differential analysis, and trajectory mapping - to nominate the regulators that flip cell fate.
What you'll do: Develop endometrial model systems: Establish, optimize, and maintain in vitro endometrial models, including primary cells, organoids, or engineered tissue systems that recapitulate peri-implantation physiology.
Core requirements: PhD in Reproductive Biology, Developmental Biology, Cell Biology, Molecular Biology, or a related field, or 5+ years of relevant academic or industry experience.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information.
- Architect the toolkit: Identify, internalize, implement, and optimize cutting-edge assays (RNAseq, scRNAseq, ATACseq, ChIP-seq, etc.) for our specific samples and instruments.