NewLimit is a biotechnology company working to radically extend human healthspan. We’re developing medicines to treat age-related diseases by reprogramming the epigenome, a new therapeutic mechanism to restore regenerative potential in aged and diseased cells. We leverage functional genomics, pooled perturbation screening, and machine learning models to unravel the biology of epigenetic aging and disease using experiments of unprecedented scale.
NewLimit is seeking an outstanding machine learning scientist to join our Predictive Modeling group. Data-driven predictive modeling is one of the key enabling technologies of our research program, allowing us to predict the outcome and prioritize the next round of experiments to guide the design of our therapies.
As a Machine Learning Scientist on our team, you will:
Work closely with genomics, sequencing, and molecular biology experts to integrate internal and external datasets to drive experiment design and predict the outcome of the next rounds of experiments.
Develop and apply novel machine learning capabilities to model the results of functional assays and large-scale pooled-perturbation screens using single-cell multi-omics (mRNA + ATAC, scCUT&TAG) data.
Serve as a technical expert, taking responsibility for the execution of sophisticated predictive modeling projects and directly influencing company-level decisions.
Contribute to the design, decision making, and implementation of NewLimit’s technology platform.
PhD in Machine Learning, Computer Science, Computational Biology, or related field or equivalent industry experience (5+ years)
Experience with machine learning applications to diverse cell biology/multi-omics datasets.
Demonstrated ability to enable team members with high quality code and artifacts.
Highly self-motivated, intellectually curious, and excited to thrive in a fast-paced, multidisciplinary, and team-oriented start-up environment.
Nice to haves
Track record of publications/accomplishments in machine learning at top-tier academic institutions or companies.
Familiarity and hands-on experience with single-cell multi-omics data.
Fluency with modern cloud computing environments.
Expertise in Python data science tools (Numpy, SciPy, Pandas, etc.) and deep learning frameworks (PyTorch, Tensorflow, Jax, etc).