Data Science Postdoc, Purdue University: Carpenter-Shen lab

Purdue University; United States; On-site; USD 52,000 - 68,000; Full time

Job summary

Purdue University’s Carpenter–Shen laboratory seeks a postdoctoral researcher to advance image-based drug discovery through data science. You will analyze high-dimensional microscopy data to extract quantitative cellular information and support new medicine discovery.

We develop methods to link image profiles with gene functions, mutations, and drug responses, with opportunities to contribute to projects on disease targets, drug repurposing, and toxicity assessment using Cell Painting and

Qualifications

• Ph.D. in a computational field with data science experience in biomedical domains.
• Expertise analyzing large-scale and/or high-dimensional biological data.
• Strong integrity, initiative, organizational & collaborative ability, and communication skills.

Skills

Biomedical data science

Large-scale data analysis

Collaborative work

Education

Ph.D. in computational field

Job description

Discover causes and cures for disease through research in the Carpenter–Shen laboratory!

Want to devote your expertise in data science to accelerate the pace at which new medicines are found? Our lab develops and applies methods to extract quantitative information from high-throughput biological images.

We seek a postdoctoral researcher to join our efforts to glean insights from large collections of images. There is much more information present in microscopy images than is commonly perceived by eye. We harvest this information, developing novel methods to characterize cellular populations at single-cell resolution. This work has the potential to transform how both the targets and therapies for disease are identified.

We aim to revolutionize the process of drug discovery in several projects, including:

• Identify the function of unknown genes and predict mutation impact, for personalized medicine
• Repurpose existing drugs to new diseases
• Identify potential therapies for bipolar disorder and psychosis, based on cell morphology changes
• Predict and classify toxicity of compounds destined for clinical trials or agrochemical use
• Develop multimodal alignment methods to link image profiles to find drug-gene matches
• Design AI agent systems to let biologists query, retrieve, and reason over large-scale image databases
• We are also open to your ideas that align well with our interests and expertise!

About you

• Ph.D. required in a computational field (Data Science, Computer Science, Computational Biology, Bioinformatics, Cheminformatics, or related) with data science experience in biomedical domains.
• Expertise analyzing large-scale and/or high-dimensional biological data is highly desired.
• You have outstanding integrity, initiative, organizational & collaborative ability, and communication skills.

About us

Our mission is to make biological discoveries by developing advanced methods to quantify and mine the rich information in images. We work as a collaborative team making discoveries to influence patient treatment. Our lab offers a professional, conscientious environment passionate about driving scientific progress.

Our lab pioneered Cell Painting, a leading image-based profiling assay used worldwide to quantify biological processes. Our open-source CellProfiler software, cited in over 23,000 papers, has enabled discoveries leading to several clinical trials, including two successful in cancer so far. We also launched a major Cell Painting consortium with ten pharmaceutical companies to produce the largest public Cell Painting dataset. Through OASIS, we created the largest public dataset combining Cell Painting, transcriptomics, and proteomics for toxicity assessment. In VISTA, we aim to systematically and scalably uncover disease phenotypes and drugs that can reverse them for disease caused by coding variants. stipend based on years of experience.

Tagged as: Computer Science, Life Sciences