RECRUITMENT PERIOD

Open date: August 12th, 2019

Next review date: Tuesday, Aug 27, 2019 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.

Final date: Friday, Dec 13, 2019 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

DESCRIPTION

The UC Berkeley Demography program is widely regarded as one of the best and most creative in the world. We occupy a unique niche in the population studies landscape, with a strong focus on formal demography, population theory, and the relationship between demographic dynamics and social, cultural, and economic dynamics.

The UC Berkeley Department of Demography seeks applicants for two postdoctoral research positions to study demography of aging and population sciences, broadly defined. The two T32 postdoctoral positions are funded by the National Institute on Aging (NIA), complementing UC Berkeley’s NIA-funded Center on the Economics and Demography of Aging (CEDA, http://www.populationsciences.berkeley.edu/ceda). The postdoctoral fellow’s research focus could include areas of Berkeley faculty research including CEDA signature areas such as mortality measurement, policy and behavioral determinants of adult health, biodemography of aging, and macro consequences of global aging.

The Fellow will be expected to work part of their time independently developing their own research portfolio in the demography of aging, and to work part of their time on collaborative mentored research with a Berkeley faculty member.

Responsibilities:
Conduct research on significant issues in some aspect of demography of aging, broadly defined
Receive grant-writing training and support in order to develop a proposal for supplemental NIH funding
Get training in responsible conduct of research
Attend departmental colloquia and other related events
If interested and qualified, teach an undergraduate course (with additional funding)
We also expect fellows to attend the Population Association of America (PAA) annual meetings, and to submit population-focused articles for publication during their time at UC Berkeley.

Minimum/Basic Qualifications required:
PhD or equivalent international degree by the time of application.

US Citizen or permanent resident.

Preferred Qualifications (by start date):
Experience in working with large data sets
Knowledge of one or two statistical analysis packages or programming (e.g., R, SAS, and/or Stata)
Qualitative and mixed methods skills
No more than five years of research experience since receipt of PhD

Appointment: The initial appointment will be made at 100% time for 1 year with a start date of September 15, 2019 through spring 2020. Thereafter, with the possibility of renewal based on satisfactory performance and availability of extramural funding and support.

To Apply: please go to the following link: https://aprecruit.berkeley.edu/JPF002266

Interested individuals should submit application with contact information for 3 individuals who have agreed to provide a reference for this specific position. All letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality (http://apo.berkeley.edu/evalltr.html) prior to submitting their letters.

This position will remain open until filled.

Please direct questions to Dr. Leora Lawton, llawton@berkeley.edu.

The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy see: http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct.

The Demography Department is interested in candidates who have research interests in subjects that will contribute to the understanding of diversity and equal opportunity in higher education through their work.

UC Berkeley has an excellent benefits package as well as a number of policies and programs in place to support employees as they balance work and family.

JOB LOCATION

Berkeley, CA

REQUIREMENTS

Document requirements

• Curriculum Vitae – Your most recently updated C.V.
• Cover Letter
• Statement of Research Interests – Including the Berkeley faculty with whom you would like to work with
• Brief descriptions of statistical skills and research experiences
• Writing Sample
• Teaching Experience and Interests – Only applies if you would like to potentially teach during the fellowship
  (Optional)

Reference requirements

3 required (contact information only)

This immediate opening is for an analyst with experience in state and local demography.  This person will be part of the small team within OFM’s Forecasting and Research Division that produces a variety of estimates and forecasts including April 1 Population Estimates, Small Area Estimates, Small Area Demographic Estimates, State Population Forecast and Growth Management Act County Projections.

This position is a senior professional and technical position responsible for providing project management, data analysis, data profiling and reporting for activities associated with career connected learning (CCL) efforts.  These efforts include outreach to data contributors and stakeholders, collaboratively creating measures and metrics; identifying data needs and linkages; and working with data based on extracts from the P20 data warehouse.  This position also leads the coordination of projects that cross units in the Forecasting & Research Division by establishing and monitoring tasks, and provides leadership on division data stewardship activities.  This position works independently, as well as part of a team of ERDC researchers and Division managers.

There is a 3-year Research Fellow position available at The University of Sussex to work on a project looking at ethnic health inequalities in later life, funded by The Nuffield Foundation.

Candidates should have strong applied quantitative skills, with a PhD in Quantitative Sociology, Demography, Social Statistics or another quantitative discipline, as well as a theoretical understanding of ethnic inequalities in health.

The Department of Environmental and Occupational Health Sciences at the University of Washington School of Public Health seeks an outstanding Post-Doctoral Research Fellow to examine the connections between heat exposure, climate, conservation interventions, and health.  The successful candidate will receive an academic appointment as a Senior Fellow. Senior Fellows at the University of Washington (UW) are considered junior faculty equivalent in rank to a Research Associate. The position is intended to extend professional training for a candidate who recently received a terminal Ph.D. degree or foreign equivalent. Opportunities for continued training are available.

The Cancer Epidemiology Program at Fred Hutchinson Cancer Research Center is offering a post-doctoral fellowship opportunity in geospatial analysis under the supervision of Dr. Margaret Madeleine, Associate Member in the Cancer
Epidemiology Program. The fellowship will focus on geospatial analyses of HPV vaccine data. The successful applicant will have the opportunity to pursue independent research and publications in addition to the main project for this fellowship, in research areas such as HPV-attributable cancer epidemiology, HPV vaccine immunoepidemiology, and immunogenetics of HPV-related cancers. Opportunities to conduct geospatial research with other faculty members at the Fred Hutch in related areas, such as colorectal cancer screening or environmental exposure assessment may also be available.

Organized by the IUSSP Scientific Panel on Family Demography and Family Law and the Institut national de la recherche scientifique (INRS).

Deadline for submission of abstracts extended to 15 September 2019.

• Read the full announcement here. 

The purpose of the IUSSP Scientific Panel on Family Demography and Family Law is to foster the study of the connection between changes in family law and changes in family structure and family dynamics while assuming as little as possible about the specifics of the connection.

Topics of interest for the seminar include, but are not limited to the following:

• Do legal restrictions that forbid divorce, impose delays or any other such constraints on divorce have an impact on the spread of unmarried cohabitation?
• Do the rules regarding marital property or maintenance duties towards ex-spouses have an impact on the choice of unmarried cohabitation over marriage?
• Did the abolition of illegitimacy for the purposes of maintenance duties and inheritance make it easier to have children without being married and is thus linked to the rise of unmarried cohabitation?
• Does the legal connection between state provided support (e.g., social assistance payments or health care services) and maintenance duties between spouses or partners have an impact on out-of-union births?
• Do the rules defining the role and duties of ‘stepparents’ towards stepchildren following separation have an impact on the formation of step-families?
• Are the legal regulations prescribing the number of ‘parents’ that a child can have linked to an increase in births following the use of reproductive technologies?
• Can the lack of legal recognition of surrogacy lead to children being given up for adoption in case of disagreement between intended parents and the surrogate mother?
• Did the introduction of same-sex marriage or same-sex registered partnerships have an impact on the processes of union formation and dissolution among same-sex couples?
• What was the impact of the introduction of adoption by same-sex couples or by single people on family formation?

The organisers will also welcome papers that address international comparisons as well as those that use innovative methodological approaches applied to relevant topics.

Online Submissions:
The IUSSP Panel on Family Demography and Family Law invites researchers in the field to submit online, by 15 September 2019, a short 200-word abstract AND upload an extended abstract (2 to 4 pages, including tables) or a full paper, which must be unpublished. To submit and fill out the online submission form, please click here: online submission form.

The seminar will be limited to a maximum of 20 completed papers. The working language of the seminar is English: abstracts and final papers should be submitted and presented in English. If the paper is co-authored, please indicate the names of co-authors at the end of the abstract. Submission should be made by the author who will attend the seminar.

Applicants will be notified whether their paper has been accepted by 30 September 2019. Authors of accepted papers must upload the full paper on the IUSSP website by 15 March 2020.

Papers submitted should be unpublished and, as for a journal or an edited book, authors, by submitting a paper, agree they will not propose it for publication to another editor until the committee makes a decision with regard to their possible publication.

Current funding for the seminar is limited; efforts are under way to raise additional funds, but the outcome at this point is uncertain. Seminar organisers cannot ensure that any travel support will be available. Applicants are therefore strongly encouraged to seek their own travel funding. Funding is contingent upon submission of a complete paper of acceptable quality by the deadline for papers.

For further information please contact Seminar Organiser Benoît Laplante (Benoit.Laplante@UCS.INRS.Ca).

IUSSP Scientific Panel on Family Demography and Family Law:
Chair: Benoît Laplante.
Members: Laura Bernardi, Minja Choe, Céline Le Bourdais, Nora Sánchez Gassen, T.V. Sekher, Joice Melo Vieira.
IUSSP Council Liaison: Suzana Cavenaghi.

DeepSpatial 2019

Co-located with 19th IEEE International Conference on Data Mining (ICDM 2019), Beijing, China

www.deepspatial.org

The significant advancements in software and hardware technologies stimulated the prosperities of the domains in spatial computing and deep learning algorithms, respectively. On one hand, advances in scalable and expressive neural network architectures and GPUs have paved the way to the recent breakthroughs in the deep learning field which has exhibited outstanding performance in handling data in space and time in specific domains such as image, audio, and video. On the other hand, the development and popularity of techniques in various domains such as remote sensing, online social media platforms, and bioengineering have enabled and accumulated large scale of spatiotemporal data over the years, which in turn has led to unprecedented opportunities and prerequisites for the discovery of macro- and micro- spatiotemporal phenomena accurately and precisely.

Nevertheless, further developments of spatial/spatiotemporal computing and deep learning call for the synergistic techniques and the collaborations between different communities, as evidenced by the recent momentum in both domains. First, fast-increasing large-scale and complex-structured spatiotemporal data requires the investigation and extension toward more scalable and powerful models than traditional ones in domains such as computational geography and spatial statistics, which has been evidenced by the fast-increasing research work on spatiotemporal data using deep learning techniques in recent few years in the spatial data computing community. On the other hand, recently deep learning techniques are evolving beyond regular grid-based (e.g., images), tree-based (e.g., texts), and sequence-based (e.g., audio) data to more generic or irregular data in space and time (e.g., in transportation, geomorphology, and protein folding), which calls for the expertise in the domains such as spatial statistics, geodesy, geometry, graphics, and geography.

The complementary strengths and challenges between spatiotemporal data computing and deep learning in recent years suggest urgent needs to bring together the experts in these two domains in prestigious venues, which is still missing until now. This workshop will provide a premium platform for both research and industry to exchange ideas on opportunities, challenges, and cutting-edge techniques of deep learning in spatiotemporal data, algorithms, and systems. Full research papers and short position papers will be accepted under the topics include, but not limited to, the following two broad categories:

Novel Deep Learning Techniques for Spatial and Spatio-Temporal Data:

• Convolutional, recurrent, and deep neural network techniques.
• Representation learning and embedding based on deep learning
• Scalable deep learning algorithms for large data.
• Interpretable deep learning for spatial-temporal data.
• Learning representation on heterogeneous networks, knowledge graphs
• Deep generative models, adversarial machine learning
• Deep reinforcement learning
• Theory of deep learning for spatio-temporal data

Novel Deep Learning Applications for Spatial and Spatio-Temporal Data:

• Remote sensing and land cover change detection/classification
• Trajectory/mobility data mining and prediction
• Spatial crowdsourcing
• Location-based social network data analytics, event prediction and forecasting
• Smart cities and ride-sharing (e.g., taxi demand forecasting)
• Other applications of deep learning

Workshop Co-Chairs
Xun Zhou, University of Iowa

Liang Zhao, George Mason University

Feng Chen, SUNY, Albany

Program Committee

• Wei Wang, (Microsoft Research)
  Ray Dos Santos, (Army Corps of Engineers)
  Arnold Boedihardjo, (DigitalGlobe)
  Chao Zhang, (Georgia Tech)
  Yanjie Fu, (MST)
  Xuchao Zhang, (NEC Lab)
  Shahriar Hossain (University of Texas, El Paso)
  Lingfei Wu (IBM Watson)
  Yanfang Ye (Case Western Reserve University)
  Yanhua Li (WPI)
  Petko Bogdanov (UAlbany)
  Yinghui Wu (WSU)
  Zhe Jiang (University of Alabama)

Important Dates:
Paper Submission: August 24, 2019
Notification of Acceptance: September 17, 2019
Camera-ready Papers: October 1, 2019
Workshop Date: November 8, 2019

Submission Instructions:
The workshop will encourage the submissions of both full research papers presents concrete research techniques and experimental results, as well as short position papers that identify and discuss the grand challenges and research opportunities on the topics of interests. All the workshop events will give enough time for attendant discussions. In particular, the workshop will consist of a series of the following events:

• Full research papers presentations: 25 minutes including 15 minutes for author presentation and 10 minutes for attendant discussion about the work.
• Short position papers presentations: 20 minutes including 10 minutes for author presentation and 10 minutes for attendant discussion about the proposed vision.

All manuscripts should be submitted in PDF format and formatted using the IEEE Proceedings templates available at: http://www.ieee.org/conferences_events/conferences/publishing/templates.html.

All the papers should be submitted through our online system here.

One author per accepted workshop contribution is required to register for the conference and workshop, to attend the workshop and to present the accepted submission. Otherwise, the accepted submission will not appear in the published workshop proceedings or in the workshop proceedings.

Contacts:
Feng Chen(SUNY, Albany): fchen5@albany.edu

Xun Zhou (University of Iowa): xun-zhou@uiowa.edu

Liang Zhao (George Mason University): lzhao9@gmu.edu

King County Metro Transit has released a Request for Proposals seeking behavioral science expertise. The primary deliverable for this RFP is development, implementation, and analysis of a set of experimental designs for applying behavioral science to decrease onboard cash payment of transit fares. Consistent with King County’s strong commitment to advancing equity, we seek to reduce onboard cash payment in a manner that maintains or enhances access to transportation for specific populations such as people with low or no income.

A secondary objective of the RFP is for King County to gain experience working with behavioral science, so that we may identify additional areas where this expertise can be applied to help us achieve results.

Please help us spread the word about this RFP by forwarding, posting, or getting it into the right hands at organizations at which you are affiliated. Or, if this opportunity is of interest to you, please submit a proposal! Bidding closes September 19 at 2PM Seattle time. You can view the RFP here:  https://procurement.kingcounty.gov/procurement_ovr/detail.aspx?bidid=4186

(Clicking on “Enter site as Guest” should take you directly to the RFP.)

This is an exciting opportunity for us at King County and, I believe, for a research partner. King County Metro Transit is one of the largest transit agencies in the country, and one of the few that is growing. We were recently named the best large transit system in North America, recognizing our achievements in innovation, equity, and sustainability. Our leadership is eager to build and use evidence to support our decision making.

Join fellow graduate students and postdocs to learn how to develop your elevator speech for job search or career exploration. An elevator speech is a clear, brief message about you. It communicates who you are, what you are looking for and how you can benefit from a company or organization.