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The INFORMS Computing Society (ICS) addresses the interface of O.R. and computing. Since their earliest days, O.R. and computing have been tightly linked. The practice of O.R. depends heavily on the availability of software and systems capable of solving industrial-scale problems: computing is the heart of O.R. in application.

ICS is INFORMS' leading edge for computation and technology. Major ICS interests are algorithms and software for modeling, optimization, and simulation. ICS is also interested in the leading edge of computing and how it affects O.R. (e.g. XML modeling standards, O.R. services offered over the web, open source software, constraint programming, massively parallel computing, high performance computing).

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Jobs of Interest to ICS

  • Atlanta, Georgia, The Centers for Disease Control and Prevention (CDC) established the 2-year Steven M. Teutsch Prevention Effectiveness Fellowship in 1995 to address an ongoing demand in public health for rigorous quantitative analysis through the recruitment, internal placement, and professional development of quantitative researchers.  Disease modeling is of increasing interest among CDC leadership.  Mathematical or computational models can allow researchers to study problems not easily examined in real life.  Through the use of models, researchers can examine the impact of a disease or intervention within a specific population.  They can then adjust the agent, population, or intervention (such as social distancing, vaccine, or quarantine) variables to test theories about relevant public health policy. The PE Fellowship is recruiting five positions specifically for modeling assignments within various programs at CDC. Applicants must have a doctoral degree in operations research, industrial engineering, mathematics, statistics, or other applied science field. Assignments focus on work related to the following types of modeling; disease transmission models, individual, compartmental, and agent-based models, spatial models, simulation and system dynamics modeling, and econometric models .   Training will be provided in; decision analysis, disease transmission modeling, advanced econometrics, machine learning and big data analysis, data visualization, and key software applications such as R, Netlogo, Python, TreeAge, etc. All doctoral degree requirements must be completed by 7/23/2021. The starting annual salary is approximately $86,000 plus Federal benefits and student loan repayment. The application period is 9/21/2020 to 1/22/2021. The fellowship begins on 8/16/2021 (this date is flexible) with an intensive orientation and training program. Interested individuals should apply now at www.cdc.gov/pef or send an email of inquiry to Dr. Adam Skelton: PEF@cdc.gov .  Phone contact is; 404-861-3882.  CDC will sponsor suitable visas for non-US citizen candidates. All applicants receive equal consideration without regard to person's race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability or genetic information, or any other non-merit factors. CDC maintains a smoke-free environment. Applicants must have a doctoral degree in operations research, industrial engineering, mathematics, statistics, or other applied science field. All doctoral degree requirements must be completed by 7/23/2021. The starting annual salary is approximately $86,000 plus Federal benefits and student loan repayment. Benefits
  • new york, New York, Wheels Up is a leading private aviation company that delivers a total aviation solution for 9,000+ members and customers throughout North America. We offer three membership options—Connect, Core, and Business—that significantly reduce the upfront cost to fly privately and enable a member to book a private plane as easily as an Uber or an Airbnb. Additionally, we provide comprehensive aircraft management and whole aircraft sales services for current and prospective plane owners.   Wheels Up gives members access to one of the world’s largest owned and managed fleets of private aircraft, totaling over 300 planes—as well as a fleet of 1,250+ Wheels Up-approved partner aircraft ranging from Light to Large-Cabin Jets. All members can also attend exclusive events and take advantage of a suite of hospitality, lifestyle, and retail benefits from some of the world’s preeminent brands.   In August 2019, we completed a Class D equity raise, giving us an enterprise valuation north of $1.1B. In January 2020, we entered into a groundbreaking partnership with Delta, which involved our company combining with Delta Private Jets to expand our fleet and offer guaranteed nationwide coverage—and which has enabled us to provide unparalleled experiences across private and commercial air travel. We also acquired our longtime partner Gama Aviation in March 2020, making us the largest Part 135 operator in the US and one of the largest private aviation operators and aircraft management companies in the world.   These developments, coupled with our previous acquisitions of Avianis, a leading tech company that has accelerated the development of our next-level digital platform, and TMC, the leading light jet charter wholesaler in the US, have made Wheels Up one of the fastest-growing and most innovative private aviation companies in the industry, capable of fulfilling any flight need.    At Wheels Up, we are realizing our vision of making private flying and the accompanying lifestyle accessible to millions of individuals, families, and businesses in the U.S. and around the world.   This Operations Research Engineer role will be part of the high performing Data Science and Analytics team whose purpose is to achieve cost savings, revenue enhancement by using advanced analytics and business optimization. This individual will be working to solve the complex business problems faced by an on-demand airline in areas of fleet planning, aircraft/crew scheduling, operational strategies and modeling.  You will be helping connect flyers to private jets in real-time, at scale.  Responsibilities Maintain and improve existing optimization algorithms and heuristics Present and communicate analytical results to various business partners Develop and implement mathematical models in matching flyers to aircraft and crew at scale Build resource planning models that enable the fulfillment process Interface and collaborate with other internal teams and business leaders to understand the business and technology/data aspects to identify appropriate opportunities and initiate new projects for business improvement using Operations Research techniques Collaborate with DevOps and Engineering to deploy said algorithms Qualifications Master’s degree (Ph.D. preferred) in Operations Research, Industrial Engineering, or related discipline. Prior experience in transportation industry (airline, cruise, rental car) highly preferred Deep understanding of integer programming and column generation techniques Deep understating of applying heuristics to solve hard OR problems Be passionate about turning the theoretical into practical and usable products for the company 3+ years building models and developing algorithms for mathematical programming  Experience in C programming under Visual Studio. Experience building cross platform a plus 3+ years programming (C/C++, Java) and commercial optimization solvers (e.g. CPLEX, Gurobi, COIN-OR, OR-Tools)  Working knowledge of Relational databases (e.g. Oracle, SQL), big data platform
  • Golden, Colorado, Aligned with the Colorado School of Mines (Mines) emphasis on Earth, Energy and Environment, the institution is focused on addressing major societal challenges at the intersection of its traditionally strong disciplinary tracks. To strengthen these efforts, Mines has initiated a search to recruit highly talented interdisciplinary faculty. We invite applications from candidates with expertise in broad disciplinary areas associated with the fields of Computational Science and Data Analytics. Candidates who have demonstrated the potential for conducting high impact research and teaching are highly desired. The successful candidates will be placed in various departments across campus where they best fit for teaching and research synergies, and joint appointments will be considered as appropriate. Specific interests for this cluster include positions in: Computational Mathematics and Data Science Methods with particular interest in algorithm analysis and development, high performance computing, and applications to scientific and engineering modeling as well as statistical and machine learning and data analysis. Business Analytics with particular interest in Business/Data Analytics, Management Science, Operations Research, Industrial Engineering, or a closely related data-analytics discipline to develop and support the quantitative business programs on campus. Applied Data Science and Machine Learning with particular interest in data science, data analytics, geostatistics, machine learning and other artificial intelligence techniques to address earth and environmental science problems of societal relevance. Computational Hydrology with particular interest in surface water hydrology, groundwater hydrology, hydrogeophysics, “big data” hydrology, or large-scale modeling of hydrologic systems. More details about the positions can be found HERE . Anticipated home departments include, but are not limited to Applied Mathematics and Statistics, Civil and Environmental Engineering, Computer Science, Economics and Business, Geology and Geological Engineering, Geophysics, Mining Engineering, and Petroleum Engineering. For further information, please contact the search chair, Prof. Kamini Singha at ksingha@mines.edu . Minimum Qualification: Ph.D. in a related discipline from an accredited program by the time the appointment begins. Strong interpersonal and communication skills. Commitment to excellence in teaching and curriculum development at both the undergraduate and graduate levels. Assistant Professor candidates must possess academic, research lab and/or industry experience and accomplishments in a related field. Associate and Full Professor candidates should have similar credentials as Assistant Professor candidates as well as national distinction and a substantial record in research, teaching and/or service. In addition, Full Professor candidates should have an established international reputation. Preferred Qualification: Successful record of teaching and research obtained via academic research, college-level teaching and/or industry or national lab experience. Commitment to diversity, inclusion and accessibility. Demonstrated success in securing externally funded grants and contracts for those applying at the rank of Associate Professor or Professor. Demonstrated record of research publications in archival journals and conference proceedings. PI126381693

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