SMB Digest Volume 19 Issue 32

NOVEMBER 12, 2019
This issue’s editor:


Information about the Society for Mathematical Biology may be found in
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Issue’s Topics:
         SMB: SMB Digest Community Forum
         SMB: Call for Nominations for 2021 Awards
         Online Colloquium: MBI, Carolyn Cho, Nov 13 Noon US EST
         Clinic: BioBridge, Jan 13-17, UC Irvine, US
         Short Course: Systems Biology, Jan 13-31, UC Irvine, US
         Article: Wiley Interdisciplinary Reviews, Systems Biology &…
         PhD Positions: Biomedical AI, U Edinburgh
         Post-doc: Modelling of Biological Systems, U Edinburgh
         Post-doc: Computational Neuroscience, U Warwick, UK
         Post-doc: Machine Learning &…, UC Santa Barbara, US
         Endowed Faculty Position: Computational Medicine, U Texas
         NSF: Request for Information, Data-Focused Cyberstructure…
         NSF: Funding Opportunity, National AI Research Institutes
         SMBnet Reminders


from: Richard Schugart <>
date: Nov 12, 2019, 2:33 PM
subject: SMB: SMB Digest Community Forum

After November 15, we will no longer be accepting advertisements
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from: Ye, Ping <>
date: Oct 30, 2019, 3:26 PM
subject: SMB: Call for Nominations for 2021 Awards

The Society is now accepting nominations for the 2021 Society prizes
through March 31st, 2020. Society members are encouraged to nominate
candidates by submitting the required materials in PDF format to the
Society Secretary, Dr. Ping Ye at The nominator
must submit:
-Contact information for the nominators and nominee,
-A letter (no more than 4 pages) describing the nominee’s qualifications
and commenting on the nominee’s scientific contributions for the society
-The nominee’s curriculum vitae, including all publications, and
-Two supporting letters.

Nominees may be affiliated with non-academic institutions, however,
please note that Society membership is a requirement for the nominator,
and nominee.

Please see details at


from: Gehring, Will <>
date: Nov 4, 2019, 1:30 PM
subject: Online Colloquium: MBI, Carolyn Cho, Nov 13 Noon US EST

MBI Online Colloquium
Wednesday November 13, 2019 at Noon Eastern Time

Carolyn R. Cho (PPDM-Pharmacometrics, Merck & Co., Kenilworth NJ)

(Mathematical) Model-Informed Drug Development

Details of how to participate can be found on the National Colloquium
webpage below. To view this live event you will need to register on the
event page. You may register at any time at:

Next Online Colloquium
Alison Etheridge, January 22, 2020


from: German Enciso <>
date: Oct 26, 2019, 2:38 PM
subject: Clinic: BioBridge, Jan 13-17, UC Irvine, US

The NSF-Simons Center for Multiscale Cell Fate (CMCF) will have a
one-week BioBridge Clinic in conjunction with the Systems Biology Short
Course at UCI in January 2020.

The BioBridge clinic will provide an accessible entry point for
mathematical scientists who wish to receive an introduction to
biological theory and practice. It will include hands-on experiments as
well as introductory lectures in molecular, cellular, and developmental
biology, providing exposure to a range of experimental model systems.
The BioBridge Clinic is open only to PhD students and postdoctoral

The BioBridge Clinic will take place the week of January 13, 2020. There
will be a $400 registration fee for the one-week Clinic, which will
include breakfast and lunch. Four Clinic fellowships, with each up to
$900, will be provided to successful applicants. The deadline to submit
an application is December 5, 2019. Please submit your application
online at

For questions, please contact


from: German Enciso <>
date: Oct 26, 2019, 2:41 PM
subject: Short Course: Systems Biology, Jan 13-31, UC Irvine, US

NIH-Funded Short Course, “Systems Biology, A Foundation for
Interdisciplinary Careers”, UC Irvine, Jan 13-31, 2020

This course covers multiple topics in systems biology and is targeted
both toward individuals with backgrounds in the mathematical,
computational or physical sciences as well as individuals with
biological or biomedical backgrounds. It emphasizes mentoring and skills
development for dealing with the unique challenges of following an
interdisciplinary career path. It is open to trainees and established
researchers. It includes lectures, small-group instruction, and
laboratory components, as well as mentoring and networking

The course will be held from Jan 13-31, 2020 on the UC Irvine campus,
followed by the Regional Conference in Systems Biology on Saturday,
Feb 1st, 2020 at UC Riverside.

Diverse, minority or disabled applicants are strongly encouraged to
apply and are eligible for financial support to cover course expenses,
travel, and lodging. Supported by a five-year NIH grant (R25-GM126365).
Space is limited. Detailed information about the course can be found at


from: WileyOnlineLibrary <>
date: Nov 1, 2019, 2:47 AM
subject: Article: Wiley Interdisciplinary Reviews, Systems Biology &…

Wiley Interdisciplinary Reviews: Systems Biology and Medicine
Early View
Online Version of Record before inclusion in an issue

Lipidomics: Current state of the art in a fast moving field
Valerie B. O’Donnell, Kim Ekroos, Gerhard Liebisch, Michael Wakelam

e1466 | Version of Record online: 23 October 2019


from: OYARZUN Diego <>
date: Oct 31, 2019, 6:07 PM
subject: PhD Positions: Biomedical AI, U Edinburgh

UKRI Centre for Doctoral Training in Biomedical AI – funded places
available for 2020 entry

The new UKRI CDT in Biomedical AI at the University of Edinburgh is
looking to recruit 12 students to start in September 2020. Students will
be fully funded for 4 years (stipend, fees and research support budget).

CDT website:

Building on a tradition of world-leading research and innovation at
Edinburgh, our Centre will train a new generation of interdisciplinary
scientists who will shape the development of AI within biomedical
research over the next decades. Our students will be equipped with all
the technical skills to realise biomedical breakthroughs through AI
while anticipating and addressing the societal issues connected with
their research.

The CDT programme follows 1+3 format. In Year 1 you will study towards a
Master by Research, undertaking a number of taught courses and taster
research projects to broaden and refine your skills and explore
different research areas. In Year 2-4 you will propose and pursue an
interdisciplinary PhD project under the joint supervision of an AI
expert and an application domain expert.

Programme benefits
-Fully funded 4-year studentship, covering tuition fees, stipend and
travel/research support.
-Extensive choice of projects at the intersection of AI, biomedicine and
social sciences, under guidance of world-leading researchers and
clinical experts.
-Interdisciplinary training programme comprising a bespoke bootcamp,
taught courses, workshops, taster projects and other activities.
-Opportunities for joint projects, research visits, internships and other
collaboration with our extensive network of research and industry
partners worldwide.
-Tailored training in public engagement, entrepreneurship awareness,
responsible innovation and leadership skills.
-Wide variety of CDT events throughout the year, including seminar
series, masterclasses, summer school, conferences, guest lectures and
industry days.
-State-of-the-art facilities and vibrant world-class research community
at the University of Edinburgh.

Entry requirements
A UK 2.1 honours degree, or its international equivalent, in computer
science, mathematics, physics, engineering or a related discipline.
Applicants from a biomedical or social sciences background with relevant
technical experience are also welcome.

CDT studentships fund 4 years of study, covering tuition fees, stipend
and travel/research support.

Deadline for international applicants: 29 November 2019
Deadlines for UK/EU applicants: 29 November 2019; 31 January 2020

More information and how to apply:
Follow us on Twitter: @BioMedAI_CDT

The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.


from: SCHUMACHER Linus <>
date: Oct 25, 2019, 5:13 AM
subject: Post-doc: Modelling of Biological Systems, U Edinburgh

Do you want to conduct research in mathematical and computational
biology, embedded in a world-leading centre for regenerative medicine?
Do you want to help us unravel the complex interplay of wound healing
and inflammation?

If you have computational and analytical skills interest in mathematical
modelling of biological systems, apple here:

You will develop a computational framework for Bayesian inference and
mathematical modelling of immune cell behaviour in wound response. We
want to create the analysis software as an open-source resource, and use
this to analyse new experimental data. We envision that the resulting
toolset will be extensible to collaboration with multiple experimental

Informal enquiries can be directed to Dr Linus Schumacher,


from: Timofeeva, Yulia <>
date: Oct 25, 2019, 8:05 PM
subject: Post-doc: Computational Neuroscience, U Warwick, UK

Research Fellow in Computational Neuroscience
Department of Computer Science, University of Warwick, UK

Fixed Term Contract for 3 years from 1 January 2020.

The appointee will work on a project funded by the MRC that aims to
develop and implement a mechanistic modelling framework for studying
regulation of synaptic transmitter release in health and disease. This
project will be led by Dr Yulia Timofeeva with the co-applicant Prof
Kirill Volynski (UCL Queen Square Institute of Neurology, London) and in
close collaboration with a number of world-leading experimental
laboratories working in the field of synaptic transmission and
information processing in the brain, that are located in Europe, USA,
Canada and Japan. The successful candidate should have a PhD, or
equivalent, in applied mathematics/theoretical physics/computer science
or a related discipline and should have excellent skills in scientific
computing. Previous experience of research in computational biology or
neuroscience is desirable.

The working environment will be in the Mathematical Science Building, in
the Zeeman Institute for Systems Biology & Infectious Disease
Epidemiology Research (SBIDER,

For further details see

Deadline for applications: 21 November 2019


from: Paul Atzberger <>
date: Oct 30, 2019, 3:22 PM
subject: Post-doc: Machine Learning &…, UC Santa Barbara, US

Post-doc Position: Scientific Computation and Machine Learning at UC
Santa Barbara

A postdoctoral position is available to work on problems at the
interface of scientific computation and machine learning in the research
group of Paul J. Atzberger, Math, UCSB. Research areas include
development of new machine learning methods, computational methods, and
applications in the sciences and engineering. A particular emphasis is
on novel ways to incorporate prior scientific knowledge, such as
physical principles, into learning frameworks and methods.

The collaborative project may also involve interactions with groups at
the Department of Energy (DOE) national laboratories or collaborating
universities. More information about this position and research can be
found at the job link below, and on Paul Atzberger’s website


POSITION: Postdoctoral Scholar In Scientific Computation and Machine
Learning At The University of California, Santa Barbara (Research Group
of Paul J. Atzberger)

A postdoctoral position in the area of scientific computation and
machine learning is available in the research group of Professor Paul J.
Atzberger in the Department of Mathematics and Mechanical Engineering at
the University of California Santa Barbara. The position involves
collaborative research on projects including the development of new
data-driven computational methods, numerical analysis, and large-scale
scientific simulation. The projects also provide potential opportunities
to be involved in activities at the national laboratories.

Postdoctoral appointments are full-time training programs of advanced
academic preparation and research training under the mentorship of a
faculty member.

Basic Qualifications: PhD Degree in Mathematics, Computing Theory or a
related discipline at the time of application.

Additional Qualifications: 1-2 years research experience or training
related to mathematics and scientific computation.

Preferred Qualifications: Prior experience would be viewed especially
favorably in the areas of large-scale scientific computation, stochastic
analysis, machine learning/data-driven methods, and/or statistical
mechanics, but are not strictly required.

The initial appointment will be for one (1) year with a possible two
(2) year reappointment if mutually agreeable.

Please apply to UCRecruit at by
December 15th, 2019 for primary consideration. Position will remain open
until filled.

Curriculum vitae, cover letter, statement of research and three letters
of reference are required for a complete application.

The Department is especially interested in candidates who can contribute
to the diversity and excellence of the academic community through
research, teaching and service.

The University of California is an Equal Opportunity/Affirmative Action
Employer and all qualified applicants will receive consideration for
employment without regard to race, color, religion, sex, sexual
orientation, gender identity, national origin, disability status,
protected veteran status, or any other characteristic protected by law.


from: Sanchez, Lorraine E <>
date: Oct 29, 2019, 10:42 AM
subject: Endowed Faculty Position: Computational Medicine, U Texas

Moncrief Endowed Faculty in Computational Medicine

The Oden Institute for Computational Engineering and Sciences at The
University of Texas at Austin is seeking a distinguished investigator to
fill a Moncrief Endowed Chair
( at the level
of Full Professor in the area of Computational Medicine. We are
particularly interested in recruiting a colleague whose research program
combines mathematical, computational, and physical approaches to solving
problems in medicine. Example areas include, but are not limited to,
medical imaging, molecular biophysics, cardiovascular science,
neuroscience, and oncology.

The Oden Institute is a unique interdisciplinary research and
educational organization focused on transforming science, engineering,
and medicine through the development and application of computation.
Research programs at the Oden Institute are diverse and build upon the
mathematical foundations for predictive science, data science, machine
learning, and (in particular) physics-based modeling using
state-of-the-art computing platforms. (Full details are available at

Applicants from quantitative science or engineering disciplines with an
outstanding record of research accomplishments, publications, and
external funding are encouraged to apply. Candidates are also expected
to have a successful record of mentoring leaders in computational
medicine, strong interest in undergraduate and graduate teaching in
computational science and engineering, as well as a commitment to
professional service. Additionally, we seek applicants who have a desire
to build collaborations with the newly established Dell Medical School.
The Oden Institute also has strong partnerships with medical
institutions across Texas, including MD Anderson Cancer Center, UT
Southwestern Medical Center, the Texas Heart Institute, and Health
Science Centers at Houston and San Antonio.

Application Instructions
Interested persons should include a cover letter, a detailed curriculum
vitae including academic and professional experience and peer reviewed
publications (please include PDF copies of your three most significant,
peer-reviewed, published manuscripts), a statement of research, a
statement of teaching philosophy, a statement summarizing past
contributions to and future plans for promoting diversity; and the names
and e-mail addresses of at least five references. Complete applications
received by December 1, 2019 will be assured full consideration. Reviews
will continue until the position is filled.

For questions, please refer to the FAQs at our website:, or you may
direct inquiries to Ms. Lorraine Sanchez at


from: Whang, Kenneth C. <>
date: Oct 24, 2019, 10:17 AM
reply-to: NSFDataCIRFI <>
subject: NSF: Request for Information, Data-Focused Cyberstructure…

The National Science Foundation is seeking community input on specific
data-intensive science and engineering research questions and challenges
and the essential data-related cyberinfrastructure services and
capabilities needed to enable that research, with particular interest in
cross-disciplinary and domain-agnostic solutions. We strongly encourage
you to read and respond to NSF 20-015: Request for Information (RFI) on
Data-Focused Cyberinfrastructure Needed to Support Future Data-Intensive
Science and Engineering Research,

The challenges of growing volumes of scientific data – their
availability, transmission, accessibility, management, and utilization –
have become urgent and ubiquitous across NSF-supported science,
engineering, and education disciplines. To inform the formulation of a
strategic NSF response to these imperatives, the RFI asks the research
community to update NSF on their data-intensive scientific questions and
challenges and associated needs specifically related to data-focused

We would like to receive an ample and broadly representative response
from across the NSF research domains and disciplines. This was the case
with successful 2017 NSF RFI on Future Needs for Advanced
Cyberinfrastructure (NSF CI 2030)[1], which informed subsequent CI
investments and a new Vision for Transforming Science Through
 As with NSF CI 2030, we intend to post the NSF 20-015 RFI responses
publicly in the spring/summer 2020 timeframe for useful reference by NSF
colleagues and the community.

To respond to this RFI please follow the guidelines outlined in the NSF
20-015 Dear Colleague Letter,

For questions concerning this RFI please contact us via This dedicated email address helps us to respond
to your questions rapidly and in a coordinated way.


Manish Parashar, Director, Office of Advanced Cyberinfrastructure (OAC)
Stefan Robila and Amy Walton, OAC Program Directors
Bill Miller, OAC Science Advisor
National Science Foundation

[1] See and


from: Henry Warchall <>
date: Oct 28, 2019, 11:36 AM
reply-to: dmsnews <>
subject: NSF: Funding Opportunity, National AI Research Institutes

A new NSF program solicitation (NSF 20-503) is now available:
National Artificial Intelligence (AI) Research Institutes

Please see
for details.

Important dates:
-Full proposals due: January 28, 2020
-Planning proposals due: January 30, 2020

From the Program Synopsis:
Artificial Intelligence (AI) has advanced tremendously and today
promises personalized healthcare; enhanced national security; improved
transportation; and more effective education, to name just a few
benefits. Increased computing power, the availability of large datasets
and streaming data, and algorithmic advances in machine learning (ML)
have made it possible for AI development to create new sectors of the
economy and revitalize industries. Continued advancement, enabled by
sustained federal investment and channeled toward issues of national
importance, holds the potential for further economic impact and
quality-of-life improvements.

The 2019 update to the National Artificial Intelligence Research and
Development Strategic Plan [1], informed by visioning activities in the
scientific community as well as interaction with the public, identifies
as its first strategic objective the need to make long-term investments
in AI research in areas with the potential for long-term payoffs in AI.

This program, a joint effort of the National Science Foundation (NSF),
U.S. Department of Agriculture (USDA) National Institute of Food and
Agriculture (NIFA), U.S. Department of Homeland Security (DHS) Science &
Technology Directorate (S&T), U.S. Department of Transportation (DOT)
Federal Highway Administration (FHWA), and U.S. Department of Veterans
Affairs (VA), seeks to enable such research through AI Research
Institutes. This program solicitation describes two tracks: Planning and
Institute tracks. Submissions to the Planning track are encouraged in
any areas of foundational and use-inspired research appropriate to NSF
and its partner organizations. Proposals for the Institute track must
have a principal focus in one or more of the following themes, detailed
in the Program Description under “Institute Track”:
-Trustworthy AI;
-Foundations of Machine Learning;
-AI-Driven Innovation in Agriculture and the Food System;
-AI-Augmented Learning;
-AI for Accelerating Molecular Synthesis and Manufacturing; and
-AI for Discovery in Physics.

[1] The National Artificial Intelligence Research and Development
Strategic Plan: 2019 Update


Subject: SMBnet Reminders

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