Postdoctoral Fellow - Machine Learning-Enabled Pathology

• Description

The Department of Biomedical Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Fellow with experience in machine learning and scientific programming. The candidate will work with a multi-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology.

Digital pathology images contain rich information on complex diseases. The goal of our efforts is to build and apply automated analytical pipelines for various types of pathology data, including histopathology images and multi-omics (e.g., genomics, epigenomics, transcriptomics, and proteomics) information.

• Qualifications

A Ph.D. in a Biomedical Informatics, Computational Biology, Computer Science, or a related field is required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Strong problem-solving and communication skills are highly desirable for this opportunity.

• Responsibilities

The postdoctoral fellow will develop and refine machine learning methods for analyzing histopathology, clinical, and multi-omics data, collaborate with our multi-disciplinary team, and publish the findings.

• Start date

This position is available immediately and can be renewed annually.

• How to Apply

Please send your curriculum vitae, two representative papers, and the names and contact information of three references to Kun-Hsing Yu, MD, PhD. (Kun-Hsing_Yu AT hms DOT harvard DOT edu)

Graduate Students

We are recruiting Ph.D. students in Harvard graduate programs, including the Bioinformatics and Integrative Genomics (BIG), Systems Biology, Biological and Biomedical Sciences (BBS) programs at Harvard Medical School, and the Health Sciences & Technology (HST) programs at Harvard/MIT. Familiarity with machine learning, basic statistical inference, and python/R programming will be helpful for a fruitful rotation.

If you are not currently an enrolled student in the programs mentioned above, please review the application information on the program websites. We cannot directly admit students to our lab.

Research Assistant/Associate

• Description

The Department of Biomedical Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a highly motivated research assistant/associate with experience in machine learning and programming. The successful candidate will play a pivotal role in conducting applied machine learning research, analyzing multiple data modalities, and developing computational tools to address critical challenges in pathology diagnosis and personalized cancer treatments.

• Qualifications

* Bachelor's or Master's degree in biomedical informatics, computer science, bioinformatics, computational biology, or a related field.
* Strong programming skills in languages such as Python or R.
* Proficiency in data analysis and machine learning techniques.
* Ability to work independently and collaboratively.
* Prior research experience in biomedical informatics or a related field is preferred but not required.


• Responsibilities

* Assist in designing novel machine learning models for analyzing pathology, clinical, and molecular data.
* Collect, organize, and analyze large-scale biomedical data sets using advanced computational techniques and statistical methods.
* Collaborate with multidisciplinary teams of scientists, clinicians, and engineers to advance research projects.
* Contribute to scientific publications, conference presentations, and grant proposals.

• Start date

This position is available immediately and can be renewed annually.

• How to Apply

Please send your curriculum vitae and the names and contact information of two to three references to Kun-Hsing Yu, MD, PhD. (Kun-Hsing_Yu AT hms DOT harvard DOT edu)