Kohane Lab

Areas of focus

• Large Language Models (LLM)
• AI to automate patient diagnosis
• Cancer treatment response

Large Language Models (LLM)

Summary

We are seeking a highly motivated and skilled Postdoctoral Fellow to join the lab of Dr. Isaac Kohane at Harvard Medical School Department for Biomedical Informatics. This position offers an exciting opportunity to contribute to cutting-edge research in the delivery of primary care using Large Language Models (LLM). The successful candidate will play a pivotal role in advancing our understanding of LLM applications in healthcare.

Job Responsibilities

• Conduct research and development activities using the Large Language Models (LLM) for medical text processing.
• Collaborate with a multidisciplinary team of researchers to design and implement novel algorithms and models for medical text analysis.
• Analyze large-scale medical datasets, extract relevant information, and develop innovative approaches to improve the accuracy and efficiency of medical text processing.
• Evaluate and validate the performance of developed algorithms and models through rigorous experimentation and benchmarking.
• Contribute to the publication of research findings in high-impact scientific journals and present research outcomes at conferences and seminars.
• Assist in mentoring and supervising researches in our lab, providing guidance and support in their research projects related to medical text processing.

Requirements

• Ph.D. in Biomedical informatics, Computer Science, Computational Linguistics, or a related field with a track record of publishing high-quality research papers in the field.
• Strong expertise and hands-on experience in using LLMs for medical text processing.
• Background in medicine or a related healthcare field is highly desirable.
• Proficient programming skills in Python and R or another relevant programming language commonly used in data science and natural language processing.
• Experience with large-scale medical datasets and familiarity with biomedical ontologies and terminologies.

Apply

To apply, please submit a cover letter, detailed curriculum vitae, a list of references, and copies of your most significant publications or preprints to jobs@zaklab.org.

AI to automate patient diagnosis

Summary

Join a project to automate diagnosis using artificial intelligence so that both patients and doctors can improve the accuracy and clinical value of diagnostic decision-making. Be a member of a multidisciplinary biocomputing team and contribute to a public-facing project.

Requirements

• Expertise in machine learning required.
• Familiarity with embeddings helpful but not required.

Apply

Send email to admin@zaklab.org.

Cancer treatment response

Summary

Rare individuals with aggressive cancers will have long-term lasting response to therapy even when most do not. We are trying to understand why. DBMI Professor and Chair Isaac Kohane seeks a postdoctoral fellow to lead the genomic analyses of these individuals (including somatic and germline genome). In the course of the analyses you will work with a small team, including scientists in the pharmaceutical industry, that will help integrate other analyses of these individuals.

Requirements

• Experience with NGS bioinformatics analyses
• Experience with R or Python scripting

Apply

Send email to admin@zaklab.org

Harvard is an Equal Opportunity Employer.