Summary

We are looking for a highly motivated Post-Doctoral Associate to join the Li Lab, specializing in cancer-related thrombosis and hemostasis research, with additional expertise in machine learning (ML) and natural language processing (NLP). The successful candidate will become part of our dynamic research team, focusing on the complex relationship between cancer and thrombosis. This role will utilize advanced computational techniques, including multi-modal clinical, imaging, and omics data, to uncover new insights and develop predictive models. Through interdisciplinary collaboration, the aim is to deepen our understanding of thrombotic complications in cancer patients and contribute to the development of innovative strategies for risk assessment, prevention, and treatment.

Job Duties

• Conducts Research:
  • Conducts in-depth literature reviews and stay abreast of the latest advancements in cancer-related thrombosis research, machine learning, and NLP.
  • Utilizes machine learning algorithms and NLP techniques to analyze large-scale biomedical datasets, including electronic health records (EHRs), genomic data, and medical literature.
  • Collaborates with clinicians and researchers to integrate multi-omics data and clinical variables for comprehensive analysis and interpretation.
• Model Development:
  • Implements predictive models to identify cancer patients at high risk of thrombosis, leveraging both traditional statistical approaches and cutting-edge machine learning algorithms.
  • Optimizes feature selection and model performance through rigorous validation and cross-validation techniques.
  • Implements natural language processing pipelines to extract relevant information from unstructured clinical texts and incorporate it into predictive models.
• Interdisciplinary Collaboration:
  • Collaborates closely with oncologists, hematologists, bioinformaticians, and computational biologists to contextualize findings and validate hypotheses.
  • Participates in research meetings, seminars, and workshops to exchange ideas and foster interdisciplinary collaboration.
  • Contributes to manuscript preparation and grant writing efforts to disseminate research findings and secure external funding.

Minimum Qualifications

• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.

Preferred Qualifications

• Prior clinical or research experience in hematology and oncology.
• A strong record of first or senior-position peer-reviewed publications.
• Demonstrate proficiency in programming languages such as SQL, Python, and R for data analysis and algorithm development, especially in software packages and libraries commonly used in informatics, machine learning, and NLP.