New physics-based computation and AI framework to understand the agressive behavior of cancer cells

By | Feature, Research

Cancer is an illness caused by an uncontrolled division of transformed cells, which can originate in almost  any organ of the body.  Cancer is not a single disease, even when it arises in the same site of the body. Tremendous variability exists in progression of disease and response to therapy among different persons with the same general type of cancer, such as breast cancer. Even at the level of a single person, cancer cells show tremendous heterogeneity within a single tumor and among a primary tumor and metastases. This heterogeneity causes drug resistance and fatal disease. The prevailing dogma is that heterogeneity among cancer cells arises randomly, generating greedy individual cancer cells that compete for growth factors and optimal environments. The rare “winners” in this competition survive and metastasize. However, tumors consistently maintain heterogeneous subpopulations of cancer cells, some of which appear less able to grow and spread. This observation prompted Gary and Kathy Luker, cancer cell biologists at the University of Michigan, to hypothesize that cancer cells may actually collaborate under some circumstances to cause disease and not just compete. The idea that single, heterogeneous cancer cells work collectively within a constrained range of variability to drive population-level outputs in tumor progression is a ground-breaking concept that may revolutionize how we approach cancer biology and therapy.

The team is using innovative approaches to extract and merge data streams from models that generate heterogeneous cell behaviors

...cancer cell biologists have teamed up with computational scientists and experts in artificial intelligence to focus the power of these fields on understanding and overcoming heterogeneity in cancer.

To understand causes of single-cell heterogeneity in cancer and conditions that motivate cancer cells to collaborate, an interdisciplinary team of scientists at UM formulated an entirely new conceptual approach to this challenging problem. The cancer cell biologists have teamed up with computational scientists and experts in artificial intelligence to focus the power of these fields on understanding and overcoming heterogeneity in cancer. Building on large, single-cell data sets unique to the team, they will combine inverse reinforcement learning, an artificial intelligence method typically applied to discover motivations for human behaviors, with computational models inferred on the basis of the physics and chemistry of cell signaling and migration. They have proposed an entirely new conceptual approach combining single cell data, physics-based modeling and artificial intelligence to single-cell heterogeneity and intercellular interactions. By discovering  testable molecular processes underlying “decision-making” by single cells and their “motivations” for acting competitively or collaboratively, this research blazes a new path to understand and treat cancer. Their high-risk, high-reward approach to understand how each cell in a population processes information and translates that to action driving cancer progression, has attracted an award of $1 million dollars by the Keck Foundation. 

The team includes Gary Luker (Radiology, Microbiology and Immunology; Biomedical Engineering), and Kathryn Luker (Radiology), who are leading the experimental studies of cell signaling and migration; Jennifer Linderman (Chemical Engineering; Biomedical Engineering); and Krishna Garikipati (Mechanical Engineering; Mathematics), who are leading the machine learning and modeling side of the project. Nikola Banovic (Electrical Engineering and Computer Science) and Xun Huan (Mechanical Engineering) are using artificial intelligence approaches to discover decision-making policies and rewards for cancer cells, working with the rest of the investigators to incorporate experimental data and physics/chemistry-based models into their approaches.

The W. M. Keck Foundation was established in 1954 in Los Angeles by William Myron Keck, founder of The Superior Oil Company. One of the nation’s largest philanthropic organizations, the W. M. Keck Foundation supports outstanding science, engineering and medical research. The Foundation also supports undergraduate education and maintains a program within Southern California to support arts and culture, education, health and community service projects. This project incorporates elements from all the W. M. Keck Foundation’s focus research areas to tackle cancer with a novel, physics-based modeling and AI-centered approach.  The idea for this project originated in the 2020 MICDE faculty workshop in AI for Physically based Bio-medicine Workshop. The workshop brought together an interdisciplinary group of faculty members to discuss ways to advance artificial intelligence and machine learning methods for biomedical problems. After seeding the idea, a subset of these researchers were awarded an MICDE catalyst grant and a MIDAS PODS grant. These funds were used to establish the proof of concept and to generate preliminary results. 

Computational science is becoming increasingly indispensable in many areas of biomedical science. While the current proposal focuses on cancer, this innovative computational framework represents a transformative leap with widespread applications in multiple other biomedical, physical, and social sciences. MICDE supports innovative and interdisciplinary projects aiming to advance the current paradigms.

Portraits of Kathryn Luker, Gary Luker, Krishna Garikipati, Jennifer Linderman, Nikola Banovic and Xun Huan

Project’s principal investigators (left to right): Kathryn Luker (Radiology), Gary Luker (Radiology, Microbiology and Immonology, and Biomedical Engineering), Krishna Garikipati (Mechanical Engineering, and Mathematics), Jennifer Linderman (Chemical Engineering, and Mathematics), Nikola Banovic (Electrical Engineering and Computer Science) and Xun Huan (Mechanical Engineering).

An Academic and Research Career Workshop for Women in Computational and Data Sciences

By | Educational, Events

The Oden Institute for Computational Engineering and Sciences at UT Austin, Sandia National Laboratories (SNL), and Lawrence Livermore National Laboratory (LLNL) are partnering to host Rising Stars in Computational and Data Sciences, an intensive workshop for women graduate students and postdocs who are interested in pursuing academic and research careers.

The workshop will be held on April 20-21, 2022, in Albuquerque, NM.

The organizers are seeking nominations for outstanding candidates in their final year of PhD or within three years of having graduated. Approximately 30 women will be selected to come to Albuquerque for two days of research presentations, poster sessions, and interactive discussions about academic and research careers, with financial support for travel provided.

The nomination form requires (1) a letter of nomination and (2) a copy of the nominee’s resume.

Full details, including the nomination form and highlights from previous events can be found here.

Please consider nominating one of your outstanding current/recent PhD students or postdocs.

Nominations are due February 18, 2022.

Helmholtz Information and Data Science Academy Visiting Researcher Grant

By | Educational, SC2 jobs

Are you a doctoral researcher or Postdoc and your research has a strong link to the (applied) data and information sciences? The Helmholtz Visiting Researcher Grant offers doctoral students and Postdocs the opportunity to do a fully-funded short-term research stay (1 – 3 months) at one of the 18 Helmholtz centers. With more than 43,000 employees and an annual budget of 5 billion euros, Helmholtz is Germany’s largest scientific organization. Its research fields include: Energy; Earth and Environment; Health; Aeronautics, Space and Transport; Matter, and Information.

The Helmholtz Visiting Researcher Grant is promoted by HiDA, the Helmholtz Information and Data Science Academy. Its aim is to enable new research collaborations, to foster knowledge exchange, and to explore new or emerging research topics in the field of information and data sciences. The program addresses researchers in both academia and in industry. It offers researchers the opportunity to get to know the Helmholtz Association of German Research Centers.

Next Application Deadline: 15 March, 2022

For more information:

Info Session on the Program (via Zoom) on Tuesday, 18 January, 2022, 14.00 – 15.00pm  CET

Sign up here:

Postdoctoral position in neuroscience in the Renart Lab, Champalimaud Foundation, Portugal

By | Educational, SC2 jobs

The Renart Lab, in the Champalimaud Centre for the Unknown (Lisbon, Portugal), is looking for candidates for a postdoc position in within a project whose goal is to understand the neural basis of simple sensory judgements using modern methods in system’s neuroscience together with theory.

Successful applicants are expected to have experience studying controlled behavior in rodents using recordings and perturbations. The project has a strong quantitative component, so experience on computational neuroscience and statistics/machine-learning methods for behavioral and neural data analysis will be highly valued.
Some recent publications and methodologies relevant for the project are:
The Champalimaud Neuroscience Programme is a vibrant research community focussed on understanding the links between neural activity and behavior. The Renart lab promotes a horizontal and collaborative environment. The position offers a competitive salary and is available immediately for a duration of 3 years (with flexibility).

Interested applicants should send their CV, a brief motivation statement and the names of at least 2 references by email to: and

Flagship Pioneering Summer Fellowship Opportunity Information Session

By | Educational, SC2 jobs

Flagship Pioneering is a life science venture creation firm based out of Cambridge, MA. Flagship’s unique venture creation process is behind companies such as Moderna, Rubius Therapeutics, Indigo Agriculture, and several dozen others.

The Flagship Pioneering Summer Fellowship Program is a one-of-a-kind opportunity to work alongside scientist-entrepreneurs at the earliest stage of ideation and develop the next breakthrough life science companies. Over the course of an immersive 12-week paid program, you will be exposed to our proprietary innovation process, connect with scientific and business leaders within our vast ecosystem, and assess employment opportunities.

Ideal candidates are creative Ph.D., M.D., M.S., or science-oriented M.B.A. students that are within 1 year of graduating upon starting the fellowship or have recently graduated. Applications are rolling, but interested candidates are strongly encouraged to apply before January 31, 2022. 

During the 1-hour information session, you will learn about Flagship Pioneering from Associates Ayse Muñiz, PhD (University of Michigan Class of 2021), and Rahi Punjabi who will discuss a new AI Fellows track launching this summer. Those with a strong background in computer science, statistics, applied mathematics, physics, and computational biology are encouraged to attend to learn more about this new track.
DateThursday, January 13, 2022
Time: 11AM-12PM

Zoom info:

Password: 756102

Idaho National Laboratory (INL) Graduate Fellowship Program

By | Educational, SC2 jobs

Idaho National Laboratory is now accepting applications for the INL Graduate Fellowship program. This program is designed to identify exceptional graduate students in research areas aligned with INL’s strategic agenda to enable the current and future mission of the lab. A collaboration between INL and universities, the INL Graduate Fellowship program provides mentoring and financial support for outstanding students who are enrolled, or plan to enroll, in graduate degree programs. Selected students will receive a salary of $60,000/year, plus tuition coverage from INL.

Flyer: INL_Graduate_Fellowship

How to apply

Applicants are invited to apply online through job posting numbers 16803 (for applicants in the fields of nuclear energy and clean energy development) and 16806 (for applicants in National & Homeland Security). Letters of recommendation should be submitted via email to

Important dates

  • February 13, 2022 – posting closes
  • May 2022 – selections will be announced