Postdoctoral Associate – The Getz Lab, Multiple Myeloma – Machine Learning

Postdoctoral Associate - Getz Lab

Overview

The Getz Lab (at the Broad Institute andMGH) is a world-leading laboratory for cancer genome analysis. We develop highly innovative, robust, and widely-used computational methods to study the molecular basis of cancer, including genomic alterations that drive primary and resistant tumors, cell-of-origin, premalignant lesions, mutational processes, activity of different pathways, and microenvironmental changes. We then follow up key findings experimentally. While the comprehensive analysis of cancer genomes is ongoing, major barriers still exist in converting this information to patient benefit and achieving the goal of personalized medicine.

Our work stands at the forefront of cancer genome science, and our research is regularly published in top-tier journals (see our work on Google Scholar and PubMed). We are dedicated to innovating and pushing the limits of what we know and what can be known in understanding the complexities of human cancer.

Environment/Lab Culture

We are an interdisciplinary group of scientists, engineers, and clinicians who work together in a mutually supportive and respectful environment. Ideas are freely shared, and contributions are highly valued. Moreover,Dr. Getzplaces a high priority on mentoring postdoctoral trainees to work toward achieving their career paths and goals, and his lab, as well as the environments at the Broad Institute and Massachusetts General Hospital, provide frequent and varied educational and skill-building opportunities.

The lab is engaged in the larger Boston-area ecosystem and the cancer research community worldwide, and provides a vibrant research environment for your contributions to be disseminated and recognized in the field. Our ability to integrate both computational and wet-lab work enables us to address key questions at a deeper and more impactful level. Indeed, we constantly use and develop new technologies to help unlock new findings.

Our ideal postdoc candidate

We are seeking a highly motivated computational postdoc to take primary leadership for developing an AI-driven prediction model for multiple myeloma (MM) that integrates multi-modal information (e.g., from whole-genome sequencing, single-cell transcriptomics, immune profiling, and clinical data) to identify patients who are likely to respond, or become resistant, to therapy.

This work will be conducted over the next 2 years (with a potential for follow-on work beyond the next 2 years) in close collaboration with Dr. Irene Ghobrial's laboratory, a world-leading group in multiple myeloma research at the Dana-Farber Cancer Institute, and will straddle the intersection among computational biology, machine learning, and clinical research. The successful candidate will bring their demonstrated expertise in artificial intelligence, machine learning, and statistical modeling to reveal insights that will better understand disease progression, therapeutic response, and mechanisms of resistance in MM, and will help to reach our collective goal of delivering precision medicine to MM by matching patients to their most likely-to-succeed therapeutic strategy.

As a member of our team, you will collaborate with other scientists, engineers, and clinicians in a collegial work environment with an emphasis on intellectual rigor. Indeed, our collective brainpower and creativity--our best asset--creates an excellent environment for deep innovation, out-of-the-box thinking, and creative problem solving. We will teach you what you do not yet know through mentoring, peer support, and many educational opportunities (e.g., floor talks, regular meetings, boot camps, journal clubs, conferences, etc.), and we will work together to make discoveries that help answer the most challenging questions in cancer.

The successful candidate will bring strong computational and statistical skills (e.g., a background in Computational Biology, Biology, Machine Learning, Statistics, Medicine, Physics, Chemistry, Engineering, Mathematics, Computer Science, or other related fields) to the lab as well as enthusiasm for learning on the job. In return, you will develop manycore competenciesto prepare you for the next stages of your career.Come and bring your energy, intellectual curiosity, and computational skills/talents to this world-class dynamic team!

Role Expectations

• Play a lead role in designing and executing data analysis strategies to drive research projects, especially pertaining to building AI-driven prediction models in MM.
• Explore and help design tools for analyzing novel data types.
• Conceive, implement, and test statistical models; analyze data from experiments.
• Present results to a variety of audiences, including non-computational researchers.
• Prepare written reports (e.g., manuscripts, grants, patents) and presentations for meetings.
• Opportunity to teach and mentor junior team members.

Requirements

• A PhD in Bioinformatics, Computer Science, Machine Learning, Engineering, Mathematics, Statistics, Physics, or a related quantitative discipline.
• 0-1+ years of post-graduate experience.
• Demonstrated experience developing and validating machine learning models.
• Experience with computational analysis, algorithm development, and statistics.
• Proficiency in at least one modern programming language. Experience with a scientific programming environment (such as Python, R, or Matlab) is preferred.
• Highly collaborative, with ability able to work on projects alongside fellow bioinformaticians, wet-lab experimentalists, and clinicians.
• Demonstrated experience with conducting rigorous and reproducible research in a fast-paced environment.
• Fast learner, analytical thinker, creative, "hands-on," team-player.
• Strong oral and written communication skills.
• Prior experience applying AI/ML methods in cancer is a plus.
• Knowledge of cancer genomics is a plus but is NOT required. Inclination to acquire such knowledge is imperative.

The expected base pay range for this position as listed above is based on a 40 hour per week schedule. Broad provides pay ranges representing its reasonable and good faith estimate of what the organization reasonably expects to pay for a position at the time of posting. Actual compensation will vary based on factors including but not limited to, relevant skills, experience, education, qualifications, and other factors permissible by law.

At Broad, your base pay is just one part of a comprehensive total rewards package. From day one, this role offers a competitive benefits package including medical, dental, vision, life, and disability insurance; a 401(k) retirement plan; flexible spending and health savings accounts; at least 13 paid holidays; winter closure; paid time off; parental and family care leave; and an employee assistance program, among other Broad benefits.

The Broad Institute is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, disability, protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

Should you need a reasonable accommodation to complete the application or interview process, please contact [email protected] for assistance.