Research Opportunities for Epidemiology Students

Brief description/abstract: This project examines HIV infection and high risk behaviors among formerly incarcerated individuals. Data from quantitative and qualitative interviews are being analyzed.
Student role/expectations/required experience: The student would assist with data analysis and searching for literature on interventions for formerly incarcerated individuals. Experience with data analysis and statistical software is required.
Start date: Monday, June 19, 2017
End date: Friday, June 29, 2018
Average amount of time per week: 10-15 hours/week
Compensation: Paid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis
Application instructions: Although the official listing will not be available until late 5/2017, if any interested students have questions, please feel free to contact Tawandra Rowell-Cunsolo at tr2301@cumc.columbia.edu.

Brief description/abstract: High mammographic breast density (MBD) reduces the sensitivity of mammography for early detection of breast cancer, and is a strong predictor of BC risk. A growing number of states, including New York, have passed legislation mandating that all women with high MBD receive written notification that informs them about the lower sensitivity of mammography and higher breast cancer risk associated with dense breasts, and advises them to consult their physicians about risk assessment and screening; > 40% of U.S. women fall into categories of high MBD that require this notification. The law may prove less beneficial in promoting BC screening in minority and low socioeconomic women, and may ultimately exacerbate disparities in breast cancer early detection and survival. This prospective study investigates a broad range of psychological outcomes and breast cancer screening behaviors in relation to disclosure of breast density information in a racially/ethnically diverse population, enriched with immigrant and low socioeconomic women.
Student role/expectations/required experience: 2 part time positions are available to participate in the following activities: conducting in-person and telephone interviews with research participants to collect epidemiologic data, research data maintenance and cleaning, statistical analysis and literature searches, create tables, graphs, spreadsheets, prepare PowerPoint presentations and scientific manuscripts writing. Bilingual (English/Spanish) individuals are strongly preferred.
Start date: Saturday, October 15, 2016
End date: Sunday, December 31, 2017
Average amount of time per week: 15-25 hours
Compensation: Paid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis, SAS
Application instructions: Please email Parisa Tehranifar directly at pt140@columbia.edu and apply to the following job posting #084742.

Brief description/abstract: Breast cancer is the most common malignancy among women in the U.S. and the primary prevention of this disease is a major public health issue. Breast cancer chemoprevention with antiestrogens, such as tamoxifen, raloxifene, and exemestane, is underutilized, despite several randomized controlled trials demonstrating a 50-65% decrease in breast cancer incidence among high-risk women. Many women may be unaware of their high-risk status due to our inability to adequately screen them in the primary care setting. Other reasons for low uptake include inadequate time for counseling, insufficient knowledge about risk-reducing strategies, and concerns about side effects. Women from racial/ethnic minorities are less likely to seek preventive measures, contributing to poorer clinical outcomes in these populations compared to non-Hispanic whites. We hypothesize that combining a patient-centered decision aid with a physician-centered decision support tool integrated into clinic workflow will improve accuracy of breast cancer risk perception, facilitate referrals for specialized risk counseling, and increase chemoprevention uptake. In our breast clinic, the chemoprevention uptake rate among high-risk women is 37%, compared to less than 5% reported for other high-risk populations. Our goal is to expand our success in the breast clinic by offering specialized risk counseling to a broader population of racially/ethnically diverse women screened in the primary care setting. We will use a novel breast cancer risk navigation (BNAV) tool, which incorporates the Gail breast cancer risk model into the electronic health record. To address patient-related barriers to chemoprevention, our research group developed an initial prototype of a decision aid, RealRisks, that allows participants to experience risk through an activity. We propose to conduct the following aims: 1a) To apply a user-centered design to evaluate and refine RealRisks for breast cancer chemoprevention; 1b) To design and evaluate BNAV for primary care providers to facilitate the identification of high-risk women eligible for chemoprevention; 2) To evaluate the effects of RealRisks and BNAV on accuracy of breast cancer risk perception and referral rates to the breast clinic among 50 high-risk women; 3) To conduct a randomized controlled trial of standard educational materials alone or in combination with RealRisks and BNAV in 300 high-risk women identified in the primary care setting and their PCPs. The primary endpoint is chemoprevention uptake at 6 months. Secondarily, we will assess accuracy of risk perception, referral rates to the breast clinic, and various patient- and physician-reported outcomes. This proposal seeks to overcome important barriers to chemoprevention uptake in the primary care setting. Given the proven efficacy of antiestrogens for primary prevention in high-risk populations, higher uptake of breast cancer chemoprevention may significantly reduce the public health burden of this disease.
Student role/expectations/required experience: 1) Recruitment of high-risk women and PCPs, data collection from participant questionnaires and clinical data from EHR; and 2) Quantitative and qualitative data analysis, manuscript preparation. Graduate student working towards a Masters,  PhD, or Postdoc (biomedical informatics, data science, epidemiology, biostatistics, or similar) with strong data analysis and computational skills and demonstrated interest in EHR data, and intervention science. Good organizational, communication, and interpersonal skills, attention to detail and the ability to work independently. The incumbent will directly report to the Principal Investigators of this project. The incumbent will support the day-to-day operations of the project, which include but are not limited to: 1) obtain, clean, and analyze aggregate data from the electronic health record, 2) calculate breast cancer risk using the Breast Cancer Surveillance Consortium risk calculator, 3) work in collaboration with PIs and study team to ensure this individual risk information will be displayed within our existing EHR Ambulatory Medicine dashboard. The incumbent will have opportunities to publish, present at conferences, write grant proposals, and in general develop his or her scientific career. S/he will perform other related duties as assigned.
Start date: Thursday, September 1, 2016
End date: Tuesday, April 30, 2019
Average amount of time per week: approximately 20 hours
Compensation: Paid ($20 per hour)
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis, SAS
Application instructions:  The Department of Biomedical Informatics together with the Department of Medicine seeks to hire a skilled individual to work as a part-time data analyst for a funded research project in breast cancer prevention. The overall objective of this project is to enhance breast cancer risk assessment using EHR data. We hypothesize that formal breast cancer risk assessment using the BCSC risk calculator may be achieved using EHR data from women screened in the primary care setting. Furthermore, we will incorporate breast cancer risk assessment into routine clinic workflow by displaying individual risk profiles within an existing EHR dashboard. We have developed a BNAV notice within an existing EHR Ambulatory Medicine dashboard. Under the “General Preventive Care” panel, individual breast cancer risk information generated from EHR data will be displayed along with high-risk criteria for breast cancer and referral information to our high-risk breast cancer prevention program. We will compare referral rates to the high-risk clinic and chemoprevention uptake before and after implementation of the EHR dashboard.

For more information, contact the project manager: Alejandro Vanegas at (212) 851-4928 or av2439@cumc.columbia.edu.

Brief description/abstract: This multi-omic project examines how the metabolome and the genome in Kazakhs contribute to the variation in obesity and to age-related changes in levels of obesity.
Student role/expectations/required experience: Student is expected to analyze the relations between the metabolome and clinical phenotype. Experience with data analysis is needed.
Start date: Sunday, February 12, 2017
End date: Thursday, January 4, 2018
Average amount of time per week: 10 hours
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis, SAS, R
Application instructions: Student should contact the PI Joseph Lee at jhl2@columbia.edu.

Brief description/abstract: Grant-funded projects focused on the role of breast density 1) in screening and early detection and related disparities, and 2) improving risk stratification for screening and prevention.
Student role/expectations/required experience: Full time data analyst position. Under direct supervision of the Principal Investigator and senior research team, the data analyst will be responsible for data quality control, database management and maintenance, data analysis, and manuscript and grant proposal preparation. S/he will also assist the Principal Investigators in manuscript preparation and presentation of materials for conferences, project and investigator meetings and in submission of IRB protocols, and other related duties as assigned.
Start date: Tuesday, November 1, 2016
End date: Monday, December 31, 2018
Average amount of time per week: Full-time
Compensation: Paid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis, SAS
Application instructions: Please email Parisa Tehranifar (pt140@columbia.edu and apply to job req# 084745.

Brief description/abstract: We are seeking a full-time data analyst to assist in the analysis of several grant-funded projects focused on the role of mammographic breast density in breast cancer prevention and control.
Student role/expectations/required experience: The data analyst will be responsible for data quality control, database management and maintenance, data analysis, and manuscript and grant proposal preparation. S/he will participate in investigator meetings, prepare reports for these meetings, assist in manuscript preparation and presentation of materials for conferences and lectures and in submission of IRB protocols. S/he will perform other related duties as assigned.
Start date: Tuesday, November 15, 2016
End date: Monday, December 31, 2018
Average amount of time per week: 35 hours (full-time)
Compensation: Paid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis, SAS
Application instructions: Please email study PI, Parisa Tehranifar at pt140@columbia.edu and apply to job posting 20024617.

Brief description/abstract: An implementation science study examining different models of service delivery for HIV positive pregnant and postpartum women and their infants.
Student role/expectations/required experience: data cleaning and analysis
Start date: Thursday, September 1, 2016
End date: Friday, June 30, 2017
Average amount of time per week: 10+ hours
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Data analysis, SAS, STATA
Application instructions: Contact Elaine Abrams; some funding possibly available.

Brief description/abstract:  This prospective cohort study enrolled 459 newly-diagnosed women and men from KwaZulu-Natal, South Africa, and followed them over an 8-month period. Participants were initially assessed prior to diagnosis, recruited and interviewed immediately following diagnosis, and followed with repeat interviews 4- and 8-months later. Analyses of the main outcome, predictors of time to linkage to care, are completed. However, many additional analyses are possible, including predictors of retention in care. Additionally, individual were assessed at each interview round on a wide range of variables relevant for HIV+ individuals, such as depressive symptoms, stigma perceptions, disclosure, functional status, intimate partner violence, social support, beliefs about ART and satisfaction with care. Cross-sectional data also are available from 2935 individuals assessed prior to HIV testing (including those who tested HIV-negative and HIV-positive). Data are cleaned and main variables are created. Data are in SPSS, but analyses could be conducted in SAS or Stata.
Student role/expectations/required experience: This is an opportunity for data analysis and manuscript writing. Project would depend on student's area of interest. Student would be expected to develop the concept for the analysis, conduct the literature review, conduct the analyses, and take the lead on the manuscript, with first authorship possible if those criteria are met.
Start date: Thursday, September 1, 2016
End date: Wednesday, May 31, 2017
Average amount of time per week: TBD
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis
Application instructions:  Contact Susie Hoffman (sh51@cumc.columbia.edu and indicate area/s of interest and data analytic experience.

Brief description/abstract: In this proposal, which is a renewal of a previously funded award, we will investigate maternal environmental factors during pregnancy and risk of childhood autism in the offspring from a national birth cohort in Finland (the Finnish Prenatal Study of Autism, FiPS-A). No previous study of autism has ever examined the proposed prenatal factors by maternal biomarkers and their relationship to perinatal complications and growth velocity of the child's head circumference during infancy. The putative risk factors include environmental toxins (including PCBs and insecticides) and infections (influenza and Chlamydia trachomatis). We aim to address these questions in pregnancies of a large sample of autism cases and matched controls using maternal serum samples that were drawn and stored in nearly all pregnancies in Finland over the course of the study. The children with autism and their matched controls have been identified from detailed databases that contain diagnoses on nearly all cases of autism in Finland. These subjects have been linked to the maternal serum samples and to other registries including data on perinatal complications. In this study, the maternal serum samples of autism cases and of matched controls will be analyzed for these environmental factors, and their occurrence during pregnancy will be compared between the cases and controls. We shall also test whether these maternal environmental factors during pregnancy are related to a select number of other pregnancy and birth complications and to abnormalities in the velocity of head circumference during infancy. This research has the potential to result in a better understanding of potential risk factors for autism and of convergen, as well as divergent, developmental pathways that lead to the illness. Since the risk factors investigated in this study are relatively common in the population, their discovery may lead to prevention of cases of autism by straightforward public measures in pregnant women, including reduction of exposure to environmental contaminants, and prevention of infections, such as influenza and sexually transmitted diseases during pregnancy. These studies could also result in an improved understanding of the mechanisms by which prenatal insults alter postnatal brain development in autism and, along with other measures, potentially target infants at high risk for the disorder for intervention. In summary, the proposed work builds on an existing national birth cohort, and is anticipated to have considerable impact on an emerging and potentially transformative area of research epidemiology and clinical/basic neuroscience, as well as lead to improvements in current public health policy recommendations for care during pregnancy.
Student role/expectations/required experience: Student is to take the lead in research studies, as well as collaborate with the investigative team. Students are expected to attend research lab meetings, participate in discussions, and conduct scientific writing. Experience in research on mental disorders is preferred but not required.
Start date: Wednesday, February 8, 2017
End date: Wednesday, October 31, 2018
Average amount of time per week: 5 hours
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis, SAS
Application instructions: Please send CV to Alan Brown at asb11@cumc.columbia.edu.

Brief description/abstract: PrEPared & Strong recruits Black men who have sex with men (MSM) and transgender women (TGW) for a study involving a new preventive treatment for HIV, Pre-Exposure Prophylaxis (PrEP). The study is being conducted in collaboration with Harlem United, which will offer medical services to participants. For those who are found to be HIV-uninfected, the study offers novel interventions to improve adherence to PrEP. The study will compare the effectiveness of an “enhanced” PrEP adherence package versus a standard PrEP adherence package, assess patterns and correlates of PrEP adherence, and monitor for changes in risk behavior among participants taking PrEP. The enhanced package seeks to combine education about PrEP with social engagement in the form of peer support and support groups in order to influence the ability to adhere to PrEP. In addition, the enhanced strategy will utilize SMS messaging reminders and social media support and info rmation groups.
Student role/expectations/required experience: project data management, data analysis, preparation of posters and manuscripts
Start date: Thursday, September 1, 2016
End date: Thursday, August 31, 2017
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis, SAS
Application instructions: Send cover letter and CV to Dr. Paul Colson at pwc2@columbia.edu. If you have questions, call Dr. Paul Colson at 646-448-0956. PrEPared & Strong is located in the Harlem Prevention Center on 125th St.

Brief description/abstract: Our research examines the mental health and developmental effects of exposure to extreme violence in the global south. Using largely unique data sets from Africa, we are investigating the association of exposure to violence with depression, posttraumatic stress disorder, grief and antisocial behavior in the many years that followed initial exposure; the impact on moral development and empathy of exposure to violence at different developmental stages--from infancy to adult; further, we will test specific hypotheses regarding intergenerational transmission of "trauma". To investigate this series of question, we have access to or have collected ourselves, data pertaining to persons 9-18 from five countries in West Africa (Liberia, Sierra Leone, Togo, Cameroon and Burkina Faso) and from post-Genocide Rwanda. Our data sets pertaining to these sites are already organized in readily accessible formats. Data from the 5 West African sites are cross sectional in nature. The Rwanda data is prospective. In 2011 we interviewed a representative sample of adult Rwandans residing in a region of the country that was heavily affected by the 1994 Genocide. In January-February of this year we re-interviewed 2011 participants (88% re-interview rate) thereby creating an opportunity for a longitudinal study. A third survey is planned for 2022.

Student role/expectations/required experience: STUDENT ROLE: Insofar as doctoral students intend to use these data as the basis for their dissertation, they will naturally be asked to formulate a research question, grounded in the previous scientific literature, that can be satisfactorily addressed by the variables assessed in one or more of the cited studies. Under the guidance of one of the investigations, most likely the Principal Investigator, EXPECTATIONS the doctoral student will be responsible for formulating and conducting the analyses pertinent to the research question, writing up the results, with due attention given to study design, measurement, analysis, findings and interpretation of the results. If the doctoral student does not plan or does not know yet whether they will have the data set serve as the basis for her/his dissertation but nonetheless wishes to have some experience analyzing these types of data, they are certainly more than welcome to do so.

Requirements: at a minimum, the student must have an intermediate knowledge of biostatistics and proficiency in testing statistical models using any one of many available statistical packages. Given the nature of the data, some knowledge of multiple regression and logistic regression and at a minium, an understanding of confounding is required.

Start date: Monday, April 24, 2017
End date: Monday, September 3, 2018
Average amount of time per week: 8+ hours
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Literature review, data analysis
Application instructions: Email Richard Neugebauer at rn3@cumc.columbia.edu.

Brief description/abstract: A study of the psychosocial impacts of genetic attributions and receipt of actual genetic test results in a dataset of families containing multiple individuals with epilepsy.
Student role/expectations/required experience: Assistance with epidemiologic data analysis, project coordination, database management, follow-up of research participants. Interested students may also learn to do qualitative research, including interview administration, coding, and analysis.
Start date: Thursday, September 1, 2016
End date: Friday, March 31, 2017
Average amount of time per week: 10 hours
Compensation: Paid
Opportunity for authorship: Yes
Skills needed: Literature review, data analysis
Application instructions: First step is to submit a CV and talk to Ruth Ottman. We have some funding now, but we are at the end of the first phase of the study. We have submitted a renewal grant that we will hear about in October/November; if it is funded, we could offer longer term support. Dissertation topics could also be developed from the data.

Brief description/abstract: We perform clinical and epidemiological research in interstitial lung disease and lung transplant outcome. We use data from a number of NHLBI-funded studies: MESA, LTOG, LTBC, as well as nationwide transplant data (OPTN/UNOS/SRTR). For details see: http://www.cumc.columbia.edu/pulmonary/research/Lederer-Laboratory
Student role/expectations/required experience: Design a hypothesis-driven study using existing data. Data analysis, manuscript composition. Experience with SAS, Stata, or R is a plus.
Start date: Saturday, April 1, 2017
End date: Thursday, December 31, 2020
Average amount of time per week: Up to you
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis
Application instructions: Send an email with your CV to David Lederer at dl427@cumc.columbia.edu.

Brief description/abstract: This study is designed to examine the magnitude and determinants of disengagement from care among HIV-positive pregnant women and infants enrolled in prevention of mother-to-child (PMTCT) services under Option B+ in Swaziland, where all HIV-positive pregnant women initiate antiretroviral therapy (ART) regardless of CD4 count. The study aims to describe engagement in care throughout the PMTCT cascade, to identify predictors of loss-to-follow-up (LTF) and disengagement in care, and identify reasons for disengagement from care among B+ for mothers and infants enrolled in PMTCT care under Option B+. Approximately 600 women and their infants enrolled in PMTCT under Option B+ at sites in the already-approved Safe Generations study will be included in this study. Alternative record and documentation sources at Safe Generations sites will be explored to determine the status of women identified as lost to follow-up. Women who are disengaged from care will be traced telephonically and/or through community-based tracing. Interviews will be conducted among a sub-sample of women to explore patterns of maternal and infant care. Understanding true retention in care under Option B+, throughout the PMTCT care cascade (pregnancy, delivery and postpartum during breast feeding), will provide critical information about the acceptability and uptake of this strategy and allow for an assessment of determinants of successful retention in care to inform the implementation of Option B+ in similar contexts.
Student role/expectations/required experience: The student may assist with data management and analysis and related study monitoring efforts, and contribute to dissemination of results when they are available in mid-2017. It is critical that the student is comfortable using SAS to merge and manipulate somewhat complex datasets.
Start date: Monday, October 3, 2016
End date: Wednesday, May 31, 2017
Average amount of time per week: 5-10 hours
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis, SAS
Application instructions: Email the study PI, Bill Reidy, at wr2205@columbia.edu.

Brief description/abstract: This is a 4-year renewal for a multi-generation, 30-year longitudinal study of families at high- and low-risk for Major Depressive Disorder (MDD). Leveraging a 30-year longitudinal dataset, we will prospectively examine whether 3 latent RDoC constructs instantiate mechanisms by which family history of MDD leads to negative outcomes in adulthood and test the intergenerational transmission of RDoC constructs. Focusing on the mechanisms of risk is a critical step to developing novel interventions to prevent negative adulthood outcomes associated with familial depression.
Student role/expectations/required experience: Help with survey, analyze existing data on family risk of depression and moderating factors. Learn to carry out diagnostic interviews if qualified.
Start date: Monday, May 1, 2017
End date: Thursday, April 30, 2020
Average amount of time per week: At least 2 days
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Literature review, Data analysis, SAS
Application instructions: Opportunity to publish from a large existing data set which includes a range of manuals. Psychosocial, clinical, religious beliefs as well as MRI, EEG data. Email Myrna Weissman at weissman@nyspi.columbia.edu.

Brief description/abstract: Should individuals continue working or retire to optimize their cognitive, functional, and psychological health? This project will explore the health effects of retirement transitions and sequences throughout the world. Given current policy interest in increasing the retirement age and economic benefits of delaying retirement, it is crucial to develop a better understanding of how the progression from work to retirement impacts health in later life.
Student role/expectations/required experience: Specific activities will include literature review, manuscript writing, and fitting longitudinal regression models. Intermediate to advanced use of Stata or R is required. Mplus knowledge is a plus, but not required. The expectation is to submit a manuscript for publication.
Start date: Monday, October 3, 2016
End date: Wednesday, March 15, 2017
Average amount of time per week: 15 hours
Compensation: Unpaid
Opportunity for authorship: Yes
Skills needed: Data analysis, STATA, R
Application instructions: Submit cover letter and CV to calvolab+cu@gmail.com by or before September 30. Applications will be reviewed on a rolling basis until the position is filled. The starting date for this research opportunity is flexible.