Computational Biology Fellowship/Post-Doc Program in Multiple Myeloma

Next-generation sequencing has revolutionized our understanding of the multiple myeloma genome, providing unparalleled resolution that has unveiled a complex and heterogeneous architecture that can significantly impact clinical outcomes. This wealth of data not only enhances our knowledge of the disease biology but also poses new scientific and logistical challenges. To tackle this complexity and develop personalized strategies, collaboration, large datasets, and advanced computational approaches are vital. The MSF computational biology fellowship/post-doc program in multiple myeloma is positioned at the intersection of computational science and oncology. Our fellows have the opportunity to develop and utilize cutting-edge computational models to predict disease progression, treatment responses, and outcomes for individuals with high-risk t(4;14) multiple myeloma at the discretion of each participating site.​​​ Fellows collaborate with existing MSF grantees to synergize with and maximize the deliverables from MSF research grants.​​ Together, we aim to decipher the intricate data landscape and triumph over multiple myeloma.

Sponsors/Mentors at each site consist of: 

  • A ​computational ​oncology ​expert
  • A translational ​medicine expert in Myeloma

Current Institutions and mentors:

  • Sylvester Cancer Center at the University of Miami
    • Mentors: Drs. Ola Landgren and Francesco Maura
  • NYU Langone Health
    • Mentors: Drs. Gareth Morgan and Aristotelis Tsirigos
  • MD Anderson Cancer Center
    • Mentors: Drs. Bob Orlowski and Linghua Wang


Accelerate research in high-risk t(4;14) Multiple Myeloma (MM): 

Accelerate research and contribute to the understanding and treatment of high-risk MM with an emphasis on the t(4;14) subtype. Projects are aimed at uncovering novel insights or developing innovative approaches to treatment. 

Generate innovative computational models:  

Post-doc/Fellows aim to create computational models that can help predict disease progression, treatment outcomes, or patient response in high-risk MM, with particular focus on the t(4;14) subset. 

Facilitate collaboration: 

MSF post-doc/Fellows and mentors aim to foster interdisciplinary collaboration between computational scientists and translational scientists. This includes validation of computational findings with laboratory scientists and clinicians.  In addition to their primary projects at their respective institutions, Fellows are also expected to meet regularly in cross-institutional collaboration with Fellows at other participating sites – potentially developing collaborative projects. 

MSF Fellowship Network

The University of Texas MD Anderson Cancer Center logo

Bob Orlowski
Linghua Wang
Minghao Dang

NYU Langone Health logo

Gareth Morgan
Aristotelis Tsirigos
Nina Murrell

Sylvester Comprehensive Cancer Center logo

Ola Landgren
Francesco Maura
Michael Durante