MICDE sponsored miRcore Biotechnology Summer Camp for the second year in a row

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miRcoreBioTec2017This year’s miRcore’s Biotechnology summer camp was a big success.  The participants had hands-on experience in a wet-lab, and with the UNIX command line while accessing U-M’s High Performance Computing cluster, Flux, in a research setting. For the second year in a row MICDE and ARC-ts sponsored the campers to access Flux as they learned the steps that are needed to run code in a computer cluster. The camp also combined theoretical thermodynamic practices that gave participants an overall research experience in nucleotide biotechnology.

miRcore’s camps are designed to expose high school students to career opportunities in biomedicine and to provide research opportunities beyond the classroom setting. For more information please visit http://www.mircore.org/summer-camps/.

[SC2 jobs] CIBC

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Senior Quantitative Developer, Quantitative Solutions – Development

Work Location: Toronto, Canada



Capitals Market Risk Management (CMRM) is led by Senior Executive Vice-President and Chief Risk Officer and is accountable on matters relating to the independent oversight of the management of risks inherent to CIBC’s activities. These risks include but are not limited to ensuring that effective processes are in place for the identification, management, measurement, monitoring and control of operational, reputation and legal, market, credit, investment and liquidity risk, collectively “CIBC Risk”, incurred by CIBC’s retail and wholesale businesses, infrastructure and corporate governance groups.

The Quantitative Solutions (QS) group is responsible for providing quantitative support for model and market data usage across Capital Markets Risk Management, including market risk VaR models used for economic and regulatory capital, and credit PFE models used for counterparty credit management. The group is responsible for methodology, development, calibration of models, market data quality and usage and explaining and troubleshooting model performance. The group is also responsible for tracking and coordinating changes to models across CMRM.

The QS Development group is responsible for developing and prototyping models for use in CMRM, including end-user tools to enhance analysis and reporting capabilities in and relating to the risk systems. The group defines the theory and practice of risk model implementation in Capital Markets Risk, with an eye both to best practices in the field, and to the practical necessities of running large systems with multiple stakeholders. The Development group communicates regularly with stakeholders regarding work in progress, and ensures work schedules are realistic, but ambitious, and that work plans are transparently communicated to stakeholders, including senior management.

Job purpose

The Senior Quantitative Analyst, Quantitative Solutions – Development is a member of a small team of quantitative analysts and developers supporting the CMRM market and credit risk system. The group is in particular responsible for:

  • Developing, testing and ensuring the sound implementation of all risk models for both market and credit risk management in the Trading operation;
  • Implementing risk and data modeling software to allow for ad hoc or ongoing business analysis. The group is expected to work closely with end user stakeholders in this case;
  • Ensuring, jointly with CMRM and QS stakeholders, that the schedule of work is prioritized, maintained and transparently communicated to all involved;
  • Ensuring a high quality of communication occurs;
  • Managing key relationships with related Technology areas, including Treasury and Risk Management Technology (TRMT) and Wholesale Bank Technology (WBT);
  • Helping to establish the strategic context in which the Quantitative Solutions group functions, ensuring this context is informed by market practice and by practical aspects of existing architecture and risk systems implementation.

Key accountabilities

  • Provide rapid development of end-user computing tools to supplement analytics of risk systems, and ad hoc tools for risk quantification.
  • Development support of legacy risk systems, prototyping vendor solutions.
  • As directed, partner with risk quants and other technology groups.
  • Communicate ideas effectively to stakeholders.
  • Ability to support quantitative development in a variety of platforms: legacy in-house analytics, interaction with the vendor systems, ad hoc tools that can be deployed to end users.
  • Meet governance and documentation standards for code changes, ensuring code can be transitioned seamlessly to other developers.
  • Support continuous enhancement of the MRM models for pricing and risk measurement of derivatives and other complex products, market risk, credit risk, and calibration of parameters.
  • Participate as a key member in cross-functional working groups, to implement joint work in support of all accountabilities.

Cross functional relationships

  • The incumbent collaborates with peers and management within Capital Markets Risk Management, WBT, TRMT, Risk Systems, Vendor developers.

Compliance requirements/responsilibities

  • As an employee of CIBC, the incumbent must comply with all applicable CIBC and Line of Business policies, standards, guidelines and controls.

Job dimensions

  • Support enhancements in quantitative risk systems through systems development work, often working independently on projects involving external stakeholders.
  • Primary clients: Risk Managers, Risk Reporting, Technology, QS – Methodology
  • Accountable for Market and Credit Risk within Capital Markets.

Knowledge and skills

  • Graduate degree in an analytic discipline, such as computer science, mathematics, statistics or physics
  • Three years’ experience in quantitative development in risk management, sufficient to formulate and develop valuation, hedging and risk measurement concepts and models or extensive software development experience
  • Strong programming skills and ability to develop in multiple programing and statistical languages (C++/C#, R etc.)
  • Familiarity with Distributed Computing, Data Science discipline, statistical modelling, machine learning and working with large datasets
  • Significant experience with risk technologies, including knowledge of common methodological issues
  • Experience in small to medium-sized projects, likely as a subject matter lead.
  • Analytical/systematic thinker. Takes a well-ordered and logical approach to analyzing problems, organizing work, and planning action.
  • Relationship builder. Develops and maintains strong relationships with internal and external customers/contacts.
  • Results oriented. Strives to achieve high levels of individual and organizational performance.


Accountability, Teamwork & Partnering
Building Trust and Relationships
Results Orientation
Creative/Innovative, Analytic/Systematic, Conceptual and Forward & Strategic Thinking
Impact & Influence
Service Orientation

Working conditions

This role operates within a normal office environment with minimal risk of ill-health or injury. Work pressures caused by tight timelines and quick decisions required on a frequent basis.

The role may require that the employee be available to work non-standard business hours and holidays as assigned by management.

How to Apply

If interested please contact Dejan Kecman at dejan.kecman@cibc.com

[SC2 jobs] Altair Engineering

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Internship Position in Machine Learning

altair_logoJob Description:

We are looking for an intern that will lead a benchmark of machine learning algorithms for engineering applications; specifically related to digital twin and predictive maintenance.

Founded in 1985, Altair is headquartered in Troy Michigan with regional operations throughout 22 countries and provides software and services to over 5,000 corporate clients representing the automotive, aerospace, government and defense, and consumer products verticals. Altair also has a growing client presence in the electronics, architecture engineering and construction, and energy markets.

Altair prides itself on its business culture that enables open, creative thinking, deeply valuing our employees and their individual contributions towards our clients’ success as well as our own each and every day. There is an entrepreneurial spirit that flows and is encouraged throughout our global workforce to develop and gather technology that is relevant to engineering and business – including employing it within our own organization.

In this position, you will be working with a team of engineers, computer scientists and mathematicians that has over 25 years of experience in developing and applying predictive and prescriptive analytics to a variety of applications including but not limited to mobile phones, planes, bikes, consumer products, whitegoods and automobiles.

The outcome of this project will shape Altair’s offerings in emerging domains such as predictive maintenance, digital twin and autonomous vehicles.


Altair headquarter building in Troy, MI; part-time telecommuting is acceptable.


1. Review public datasets and choose a subset to be used for benchmarking.
2. Review available predictive modelling/machine learning tools and identify the ones to include in the benchmark.
3. Become familiar with the predictive modelling/machine learning implementations in Altair such as the ones in HyperStudy.
4. Conduct the benchmark for performance and accuracy
5. Make suggestions for methods and applications.


  • Graduate student in data science or related fields.
  • Bachelor of Science Degree in Mechanical Engineering, Aerospace Engineering, Materials Sciences or related fields.
  • Experience with data analysis and prediction modelling tools and languages such as R, Python, SAS, Matlab, Tableau, MicroSoft Azure.
  • Experience in engineering or scientific work is preferred.
  • Experience with machine learning, predictive and prescriptive modelling methods.
  • Excellent communication skills both written and verbal.
  • Good presentation skills.

Application procedures:

To apply please contactFatma Y. Koçer-Poyraz at fatma@altair.com

Siqian Shen (IOE) to receive an Early Career Award from the Department of Energy

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siqian-shen-featuredMICDE Associate Director Siqian Shen has been selected to receive an Early Career Award for the Department of Energy Office of Science by the DoE Office of Advanced Scientific Computing Research. The objective of her proposal titled “Extreme‐Scale Stochastic Optimization and Simulation via Learning‐Enhanced Decomposition and Parallelization” is to develop an efficient and unified framework that integrates machine learning with discrete optimization and risk‐averse modeling. The models considered represent a broad class of complex decision‐making problems, where 0‐1 or continuous decisions are made before and/or after knowing multiple and potentially correlated sources of uncertainties. This research will shed new light on the traditional decomposition algorithms for high‐performance computing.

Prof. Shen was recently promoted to Associate Professor of Industrial and Operations Engineering. To learn more about her research please visit http://micde.umich.edu/faculty-member/siqian-shen/.

The Early Career Award program from the US Department of Energy is a funding opportunity for researchers in universities and DOE national laboratories to support the development of individual research programs of outstanding scientists early in their careers. For the past 8 years this program has helped stimulate research careers in the disciplines supported by the DOE Office of Science. These include Advanced Scientific Computing Research (ASCR); Biological and Environmental Research (BER); Basic Energy Sciences (BES), Fusion Energy Sciences (FES); High Energy Physics (HEP), and Nuclear Physics (NP).

COMPUTATIONAL SCIENCE AROUND U-M: Increasing women participation in computing education

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5 faculty members recognized for working towards increasing women participation in computing education

Four faculty members of the University of Michigan’s division of Computer Science Engineering (CSE) and one from the department of Naval Architecture and Marine Engineering (NAME) were awarded second place in the NCWIT Extension Services Transformation (NEXT) Awards. NAME lecturer Laura Alford, along CSE faculty members Dr. Mary Lou Dorf, Dr. Valeria Bertacco, Dr. Amir Kamil and Dr. William Arthur were recognized for showing outstanding achievement as clients of NCWIT Extension Services of Undergraduate Programs(ES-UP). ES-UP is”a program that helps academic departments of computing develop high-impact strategies for recruiting and retaining more women students with advice that is customized to local needs and conditions”. More…

MICDE Annual Symposium – Poster Competition Winners

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Fifty-six posters were submitted to the 2017 MICDE symposium poster competition.

Last week’s MICDE annual symposium included a poster competition for students and postdocs. The event featured 56 posters that highlighted the interdisciplinary nature of the institute. (Some of the posters were described in a story in the Michigan Daily). All of the titles and abstracts submitted are in this spreadsheet.

Victor Wu, Ph.D. Candidate in the department of Industrial and Operations Engineering, won first place and $500 for his poster “Multicriteria Optimization for Brachytherapy Treatment Planning.” Wu and co-authors Epelman, Sir, Pasupathy, Herman and Duefel, introduced an efficient Pareto-style planning approach and intuitive graphical user interface that enables a planner or physician to directly explore dose-volume histogram metric trade-offs for brachyotherapy treatment – a common method for treating cancer patients with radiation.

Sambit Das, Ph. D. Candidate of Mechanical Engineering, earned second place and a $250 prize for his work on “Large Scale Electronic Structure Studies on the Energetics of Dislocations in Al-Mg Materials System and Its Connection to Mesoscale Models

Third place, also with a $250 prize, went to Joseph Cicchese, Ph. D. Candidate in the Department of Chemical Engineering, for his poster titled “How to optimize tuberculosis antibiotic treatments using a computational granuloma model. Cicchese and co-authors Pienaar, Kirschner and Linderman, proposed a method of combining an agent-based and multi-scale model of tuberculosis granuloma formation and treatment with surrogate-assisted optimization to identify optimal tuberculosis treatments.


SC2 presents the 2017 NVIDIA Visualization Challenge

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Courtesy of S. Alben (Mathematics)The Scientific Computing Student Club (SC2) and NVIDIA are presenting a Visualization Challenge, with prizes including two NVIDIA and sponsorship to enter present your results at the Scientific Visualization Showcase at Supercomputing ’17. If you are an U-M student doing research that involves coding, simulations, or data analysis, chances are you have a lot of data to show. But what is the best way to do it? What is the best way to reach your audience and convey your message? As the old adage says “a picture is worth a thousand words”, so making your data interactive, showing it in 3D, or making a video are a few options.

More information and registration at micde.umich.edu/sc2/challenge2017. Registration deadline is March 1, 2017.



Michigan Biological Software Team to compete at iGEM with MICDE support

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MICDE is pleased to announce its support of the Michigan Biological Software Team (MiBioSoft), for its attendance at the 2017 International Genetically Engineered Machine (iGEM) competition in Boston.

Founded in 2014, MiBioSoft is a student-run organization at the University of Michigan that develops software for use in scientific research, with a focus on synthetic biology. It seeks to provide its members with opportunities to not only improve their skills as software designers, but also to improve their communication and management skills by bringing together students from a variety of backgrounds including Biology, Mathematics, Computer Science, and Chemistry.

MiBioSoft competes annually in the software track of the iGEM competition, where research teams from around the world present their results over the course of a three-day conference. During the first two years at the competition, the team was awarded bronze medals. In 2016, MiBioSoft received Best Software Project award as well as a gold medal for their protocol catalog, ProtoCat, in a competition that featured over 300 teams from more than 40 countries, with more than 5,000 participants in total.

About Protocat

Protocat is protocol catalog software developed by MiBioSoft students to address the issue of reproducibility in synthetic biology. Like many innovative ideas, it began because of a problem. Studies have estimated that only 10-25% of published scientific results are reproducible. A 2014 survey conducted by the Michigan Software team confirmed that the repeatability problem exists in synthetic biology, with every scientist surveyed reporting prior struggles with replicating protocols.

ProtoCat 3.0 is a free database of crowd-sourced protocols designed to make existing protocols more repeatable and enable more accurate computational models of biological systems. MiBioSoft believes this can most efficiently be accomplished with a commitment to open source protocols and a broader more active community of digital troubleshooters. ProtoCat 3.0 works to establish such a community by giving anyone with an internet connection or smartphone access to a repository of synthetic biology protocols collected from all over the world. Additionally, ProtoCat 3.0 encourages the development of higher quality, more repeatable protocols by allowing users to document, rate, review, and edit existing methods.

New MICDE Catalyst Grants to fund research projects in computational science

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micde2016symposiumfrontpageThe Michigan Institute for Computational Discovery & Engineering (MICDE) seeks proposals for innovative research projects in computational science that combine elements of mathematics, computer science, and cyberinfrastructure. Of interest is computational science research in any emerging area, including but not limited to (a) applications such as neuroscience, ecology, environmental science, evolutionary biology, human-made complex systems, urban infrastructure and energy; and (b) frameworks for scientific software, and exascale computing. Priority will be given to high-impact projects with potential to attract external funding. MICDE expects to fund 3-4 one-year projects at up to $100,000 each.

An informational session will be held on Thursday, Nov. 10, 2016 at 2:00 p.m. in Room D of the Michigan League (911 N. University).

For more information go to http://micde.umich.edu/grants/catalyst-grants/

MICDE affiliated faculty Monica Valluri (Astronomy) recognized for her outstanding research and teaching achievements

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valluriMonica Valluri, a Research Associate Professor in the Department of Astronomy, has been honored with the U-M Research Faculty Achievement Award for her outstanding research and teaching career in theoretical galaxy dynamics. She uses numerical calculations and simulations to probe galactic phenomena, including supermassive black holes and dark matter halos,two types of invisible matter whose presence is inferred primarily from their gravitational effects on stars and other visible matter.

Valluri earned a Ph.D. in astrophysics at the Indian Institute of Science in Bangalore, did postdoctoral research at Columbia University and Rutgers University, and joined the U-M faculty in 2007.

In addition to developing a more accurate method to determine the masses of SMBH, Valluri has transformed our understanding of galactic bars — elongated cigar-shaped clusters of orbiting stars that exist in many spiral galaxies, including the Milky Way. She demonstrated the traditional view of how stars move in bars is incomplete and that neglecting the effects of galactic bars can cause large errors in the measurement of black hole masses and host galaxy properties. Her work soon will be applied to data being gathered by the European Space Agency’s Gaia space observatory and is expected to verify or refute important predictions of the dominant paradigm regarding the nature of dark matter.

Valluri has published 42 journal articles. In addition to creating and teaching undergraduate astronomy and earth and space science courses, Valluri has taught at the Michigan Math and Science Scholars camp for high school students on a number of occasions. She has served on five doctoral committees and mentored 17 undergraduates. She also founded and organizes Conversations on Equity and Inclusion in Astrophysics and has served on the astronomy department’s curriculum committee and Michigan Institute for Research in Astrophysics planning committee. Valluri is chair of the American Astronomical Society Division of Dynamical Astronomy and a member of the Astronomical Society of India and International Astronomical Union.

With information from the record.umich.edu