Dr. Matthew J. Simpson
Professor, Queensland University of Technology, Science & Engineering, Mathematical Sciences, Applied & Computational Mathematics
Research Website
Mathematical and experimental models of cell invasion with fluorescent cell cycle indicators
Thursday, Oct. 31, 2 PM, RRI 101
Abstract: Fluorescent cell cycle indicators, such as FUCCI, allow us to visualize the cell cycle in individual cells. FUCCI reveals real-time information about cell cycle dynamics in individual cells, and can be used to explore how the cell cycle relates to the location of cells, local cell density, and different microenvironments. In this talk I will describe how FUCCI technology can be incorporated into continuum and discrete models of cell invasion. Using experimental data from two-dimensional cell invasion assays with FUCCI-transduced melanoma cells, we show how mathematical models can be used to predict key features of the experiments. The models we present are also amenable to travelling wave analysis, and some key highlights of this analysis will also be presented and discussed.
Monday, October 28, 2019
Survey of Christian, Muslim, Jewish, or Atheist Students in Science
I am a professor in the School of Life Sciences at Arizona State University and my research group is interested in understanding the experiences of graduate students from diverse religious backgrounds. We are conducting scholarly interviews with biology graduate students who identify as Christian, Muslim, Jewish, or Atheist about their experiences in the biology community. We would like to understand the range of experiences students have with these identities to improve the training of scientists from many different backgrounds.
We are offering students a $15 gift card to conduct a one-hour Skype interview with our researchers. All information will remain completely confidential. If you are interested in participating, please follow this link and fill out our short survey and our research team will contact you shortly to schedule your interview: https://tinyurl.com/y5ocuj38
If you have any questions or concerns about the research, you can contact my postdoctoral researcher Elizabeth Barnes at liz.barnes@asu.edu
Sincerely,
Sara Brownell, PhD
Associate Professor
School of Life Science
Arizona State University
sara.brownell@asu.edu
M. Elizabeth Barnes, PhD
Postdoctoral scholar
School of Life Science
Arizona State University
Liz.barnes@asu.edu
We are offering students a $15 gift card to conduct a one-hour Skype interview with our researchers. All information will remain completely confidential. If you are interested in participating, please follow this link and fill out our short survey and our research team will contact you shortly to schedule your interview: https://tinyurl.com/y5ocuj38
If you have any questions or concerns about the research, you can contact my postdoctoral researcher Elizabeth Barnes at liz.barnes@asu.edu
Sincerely,
Sara Brownell, PhD
Associate Professor
School of Life Science
Arizona State University
sara.brownell@asu.edu
M. Elizabeth Barnes, PhD
Postdoctoral scholar
School of Life Science
Arizona State University
Liz.barnes@asu.edu
QCB Colloquium | Dr. John H. Maddocks
Dr. John H. Maddocks
Professor, EPFL Lausanne, Switzerland, Laboratory for Computation & Visualization in Mathematics & Mechanics
Lab Website
The cgDNA sequence-dependent coarse-grain model of dsDNA: Bridging the scales from Molecular Dynamics to Bioinformatics
Tuesday, Oct. 29, 3:15 PM, MCB 102
Abstract: The cgDNA+ coarse-grain model of DNA (lcvmwww.epfl.ch/research/cgDNA/) can now accurately predict the sequence-dependent statistical mechanics properties, for example shape and stiffness (or equivalently first and second moments of the equilibrium distributions), of double-stranded DNA fragments of arbitrary sequence. At scales of tens of base pairs these predictions can be compared with Molecular Dynamics simulations and they agree very well. However the efficiency of the cgDNA+ model allows genome length scales to be scanned in order to identify mechanically exceptional sequence fragments, including in an epigenetically modified sequence alphabet.
Professor, EPFL Lausanne, Switzerland, Laboratory for Computation & Visualization in Mathematics & Mechanics
Lab Website
The cgDNA sequence-dependent coarse-grain model of dsDNA: Bridging the scales from Molecular Dynamics to Bioinformatics
Tuesday, Oct. 29, 3:15 PM, MCB 102
Abstract: The cgDNA+ coarse-grain model of DNA (lcvmwww.epfl.ch/research/cgDNA/) can now accurately predict the sequence-dependent statistical mechanics properties, for example shape and stiffness (or equivalently first and second moments of the equilibrium distributions), of double-stranded DNA fragments of arbitrary sequence. At scales of tens of base pairs these predictions can be compared with Molecular Dynamics simulations and they agree very well. However the efficiency of the cgDNA+ model allows genome length scales to be scanned in order to identify mechanically exceptional sequence fragments, including in an epigenetically modified sequence alphabet.
Monday, October 21, 2019
Post-doc and Bioinformatician positions available in NYC
The Bunyavanich Lab welcomes talented, self-motivated individuals who can fulfill the responsibilities and requirements below to apply for positions in our lab at the Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY. The successful applicant will be part of an interdisciplinary team led by Dr. Supinda Bunyavanich that applies computational analysis and bioinformatics to interpret multi-scale data generated from subjects with asthma and allergic diseases. Our researchers receive generous packages, including robust salaries and a wealth of opportunities to participate in academic activities here at the Institute for Data Science and Genomic Technology and more broadly at regional and national workshops and conferences. We are located in the heart of Manhattan, and Mount Sinai is one of the oldest and largest teaching hospitals in the US.
Responsibilities:
• Analyze high-throughput sequence data.
• Develop and implement methods to analyze these data.
• Maintain large datasets linked to clinical data.
• Communicate progress with PI regularly and contribute to the success of the research team.
• Develop and maintain productive collaborations within Mount Sinai and with outside researchers in academia and industry.
• Publish and present novel research findings in academic journals and conferences
• Some supervision of trainees and technical staff may also be required.
Requirements:
• Degree in bioinformatics, computer science, computational biology, genomics, or a related field.
• Outstanding programming skills in R, Python, and Unix shell scripting.
• Excellent track record of analyzing sequence data. Experience with clinical cohorts and microbiome analysis a plus.
• Demonstrated knowledge of statistics and statistical genetics. Familiarity with genomic data tools, repositories, and databases.
• Strong attention to detail and solid analytical skills.
• Ability to work hard and independently while contributing to the team effort and adhering to deadlines.
• Excellent oral and written communication skills with track record of productive collaborations.
• Demonstrated ability to work concurrently on several projects, and good understanding of analytic complexities to do independent research as well as assist other researchers.
The Institute for Data Science and Genomic Technology at the Icahn School of Medicine at Mount Sinai seeks to comprehensively integrate the digital universe of information into research, training, and patient care and to develop programs that advance the future of healthcare and data science.
Interested and qualified candidates should submit a CV and detailed letter of interest to Dr. Supinda Bunyavanich (Supinda.Bunyavanich at mssm.edu).
Responsibilities:
• Analyze high-throughput sequence data.
• Develop and implement methods to analyze these data.
• Maintain large datasets linked to clinical data.
• Communicate progress with PI regularly and contribute to the success of the research team.
• Develop and maintain productive collaborations within Mount Sinai and with outside researchers in academia and industry.
• Publish and present novel research findings in academic journals and conferences
• Some supervision of trainees and technical staff may also be required.
Requirements:
• Degree in bioinformatics, computer science, computational biology, genomics, or a related field.
• Outstanding programming skills in R, Python, and Unix shell scripting.
• Excellent track record of analyzing sequence data. Experience with clinical cohorts and microbiome analysis a plus.
• Demonstrated knowledge of statistics and statistical genetics. Familiarity with genomic data tools, repositories, and databases.
• Strong attention to detail and solid analytical skills.
• Ability to work hard and independently while contributing to the team effort and adhering to deadlines.
• Excellent oral and written communication skills with track record of productive collaborations.
• Demonstrated ability to work concurrently on several projects, and good understanding of analytic complexities to do independent research as well as assist other researchers.
The Institute for Data Science and Genomic Technology at the Icahn School of Medicine at Mount Sinai seeks to comprehensively integrate the digital universe of information into research, training, and patient care and to develop programs that advance the future of healthcare and data science.
Interested and qualified candidates should submit a CV and detailed letter of interest to Dr. Supinda Bunyavanich (Supinda.Bunyavanich at mssm.edu).
Research and Fellowships Week
Research and Fellowships Week is an annual event hosted by USC’s Academic Honors and Fellowships, the Graduate School and the Office of Postdoctoral Affairs. The goal of the week is to discuss opportunities that support research, graduate study, language learning, teaching and internships within the U.S. and abroad. The sessions are open to students of all academic levels, staff and faculty, attendees participate in interactive panels and workshops to explore USC programs and external post-graduate possibilities.
The following activities are geared towards graduate students:
Monday, November 4
Fellowships for PhD Students in Health Fields, 12:00-12:50pm, HSC Norris Medical Library, West Conference Room
“The Novelty Moves”: How to Pitch Your Research to Potential Funders….and Beyond, 1:00-1:50pm, Doheny Library (DML) 241
Tuesday, November 5
Fellowships for International PhD Students, 1:00-1:50pm, Doheny Library (DML) 241
USC Advanced PhD Fellowships, 2:00-2:50pm, Doheny Library (DML) 241
Wednesday, November 6
Research with Impact: Data and Bibliometrics, 2:00-2:50pm, Doheny Library (DML) 241
Thursday, November 7
Focus on the NSF Graduate Research Fellowship Program, 1:00-1:50pm, Doheny Library (DML) 241
Friday, November 8
Fulbright U.S. Student Program,11:00-11:50am, Hedco Neurosciences Building (HNB 100)
More information about Research and Fellowships Week is available here: https://ahf.usc.edu/events/rfw/
The following activities are geared towards graduate students:
Monday, November 4
Fellowships for PhD Students in Health Fields, 12:00-12:50pm, HSC Norris Medical Library, West Conference Room
“The Novelty Moves”: How to Pitch Your Research to Potential Funders….and Beyond, 1:00-1:50pm, Doheny Library (DML) 241
Tuesday, November 5
Fellowships for International PhD Students, 1:00-1:50pm, Doheny Library (DML) 241
USC Advanced PhD Fellowships, 2:00-2:50pm, Doheny Library (DML) 241
Wednesday, November 6
Research with Impact: Data and Bibliometrics, 2:00-2:50pm, Doheny Library (DML) 241
Thursday, November 7
Focus on the NSF Graduate Research Fellowship Program, 1:00-1:50pm, Doheny Library (DML) 241
Friday, November 8
Fulbright U.S. Student Program,11:00-11:50am, Hedco Neurosciences Building (HNB 100)
More information about Research and Fellowships Week is available here: https://ahf.usc.edu/events/rfw/
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