CONVOCATORIA ABIERTA | PROGRAMA IDI-BD2K | VERANO 2022 | FECHA LÍMITE EXTENDIDA 31 DE MARZO

C O N V O C A T O R I A A B I E R T A 📢

El programa Increasing Diversity in Interdisciplinary Big Data to Knowlege (IDI-BD2K) desea anunciar que ha abierto la convocatoria para participar en un internado de verano en una de las instituciones adscritas: University of California, Santa Cruz (UCSC), University of Pittsburgh (UPitt) y Harvard University

Requisitos:

Estudiante subgraduado/a a tiempo completo en la UPR-Río Piedras.
Interés en trabajar en ciencia de datos y/o realizar investigación biomédica.
Cursos aprobados en Ciencia de Cómputos y Estadísticas.
Completar la solicitud en línea en todas sus partes.
Proveer dos (2) cartas de recomendación y transcripción de crédito no oficial.

Para solicitar, favor de completar la solicitud en línea: https://tinyurl.com/applybd2k2022
Fecha límite: 28 de febrero de 2022

Summer Research Opportunity: IQ BIO REU

The University of Puerto Rico at Rio Piedras will host a nine week paid research internship for undergraduate students. The NSF-sponsored program offers training and practice for fluency in quantitative skills, data analysis, and bioinformatics and myriad opportunities for career development.

Congratulations to Dr. Juan Ramirez Lugo and our very own Dr. Patricia Ordoñez for obtaining this award.

http://iqbioreu.uprrp.edu/

Summer 2019 Internships

The IDI-BD2K has funding for 2 internships for each of the following partnering universities: Harvard University, University of Pittsburgh, and University of California Santa Cruz, for a total of 6 internships. University of Pittsburgh has up to 9 more university internships available, to which we can recommend you, for a total of 15 internships. The internships are from 8-10 weeks. If you are interested in participating, please apply by Wednesday, January 30, 2019 at the following website:

https://goo.gl/forms/1HLXg90x6qfBJY5t2

Looking forward to receiving you applications,

The IDI-BD2K Leadership team

Diversity in Data and Computer Science

Diversity flyerA conversation with David Boone, PhD, Assistant Professor of the University of Pittsburgh where he will introduce STUDENT AND FACULTY INTERNSHIPS in the Department of Biomedical Informatics at his university through the Increasing Diversity in Interdisciplinary Biomedical Big Data to Knowledge (IDI-BD2K) Program of the UPRRP. A brief overview of the IDI-BD2K DATA SCIENCE PROGRAM will be given. Finally, he will engage in fish bowl conversation with Dr. Patricia Ordóñez, Associate Professor of the Department of Computer Science, and the audience to talk about his career path and DIVERSITY IN DATA AND COMPUTER SCIENCE. Topics will include the Imposter Syndrome, Unconscious bias, and Stereotype Threat.

Fellowship opportunity for recent graduates

The Opportunity:

The National Institute of Allergy and Infectious Diseases (NIAID) is offering an exciting fellowship opportunity in data science for recent undergraduate or graduate students (Bachelor’s, Master’s, or Doctorate) who are interested in acquiring a unique training experience involving rotations throughout the Institute to either intramural or extramural programs engaged in data-intensive science.  The rotations will provide a broad overview of the data-intensive science that NIAID supports and train fellows through hands-on experience in how to apply and manage big data, bioinformatic strategies, computational platforms and tool development towards the study of infectious, immunological, and allergic diseases.  The application deadline is October 2nd.

If you know of anyone who may be interested, please feel free to share this opportunity with them.

Please see the link below for additional information on how to apply:

https://www.zintellect.com/Posting/Details/3600

Alexandra Carruthers Ferrero: Nuestros estudiantes en internados de verano 2017

Hi! I am Alexandra Carruthers Ferrero. I am currently an undergraduate physics major at the University of Puerto Rico, Río Piedras Campus. This summer, I participated in Harvard T.H. Chan School of Public Health‘s Summer Program in Biostatistics and Computational Biology through IDI-BD2K (Increasing Diversity in Interdisciplinary Big Data to Knowledge). Thanks to this incredible opportunity, I was able to work on a public health research project under the mentorship of Dr. Cory Zigler and Dr. Chanmin Kim. The project focused on tracking air pollution from coal power plants throughout the United States. We worked with time-varying data to construct linear regression models and learn how the emissions of certain power plants spread and impact populations throughout the country. Traditionally, chemical and physical models are used to study the spread of air pollution. Therefore, another key point of our project was to compare the results of a purely data based statistical model with those of chemical and physical models. In addition to working on a research project, the program provided us with professional workshops and courses in biostatistics and epidemiology.

I cannot say enough how grateful I am to have had the opportunity to take classes and research in the school of public health this past summer. It provided an environment for not only professional but also personal growth. I wholeheartedly recommend others to participate!

Jovaniel, Alexandra, David and Dr. Chanmin Kim show us the Zigler Lab

Stephanie Colón Marrero: Nuestros estudiantes en internados de verano 2017

My name is Stephanie Colón Marrero and I am a Biology undergraduate student at University of Puerto Rico, Rio Piedras Campus (UPR-RP). This past summer I participated in the Internship in Biomedical Research, Informatics, and Computer Science (iBRIC) from the Department of Biomedical Informatics at the University of Pittsburgh. I had the opportunity to work alongside Dr. Qiming Jane Wang and Dr.
Sahdeo Prasad, from the Department of Pharmacology and Chemical Biology at the University of Pittsburgh School of Medicine, on a research project that aimed to exploit the therapeutic potential of combining protein kinase D inhibitors with chemotherapeutic agents for prostate cancer treatment. We first studied the potential of these drugs to inhibit cell proliferation and cell migration, fundamental biological processes implicated in cancer development and progression, by performing cell viability and wound-healing assays, respectively. Our findings contribute to a mouse prostate cancer metastasis model currently being developed in the Wang laboratory.

At the end of the program, I participated in the Summer Research Symposium at Duquesne University. I encourage every student interested in bioinformatics and biomedical research to take part in the research opportunity offered by the Increasing Diversity in Interdisciplinary Big Data to Knowledge (IDI-BD2K) program. Participating in research programs, like iBRIC, provides valuable tools that could improve significantly your personal and professional growth.

Stephanie Colon presenting at the Summer Research Symposium at
Duquesne University.

Israel O. Dilán-Pantojas: Nuestros estudiantes en internados de verano 2017

Hola soy Israel O. Dilán-Pantojas, estudiante del programa de bachillerato de estudios generales, tengo la meta de completar una segunda concentración en Ciencias de Cómputos. Este próximo año sería mi 7mo año de estudio en la Universidad de Puerto Rico, y actualmente participo activamente en grupos de investigación de Biomedicina y Bioinformática.

Este verano he estado trabajando, con investigación en el campo de Descubrimiento Causal con modelos gráficos, en el Centro para el Descubrimiento Causal bajo la tutela del Dr. Greg Cooper y la mentoria del estudiante graduado Bryan Andrews. Este campo busca identificar correctamente la orientación de de relaciones de causalidad, es decir si un agente o causa A controla el resultado de una variable dependiente o efecto B. Ósea, A y B no están casualmente relacionado (A    B),  A causa B (A -> B), B causa A (A <- B) o ambos A y B están mediados por otro agente que los causa a ambos (A<->B). Actualmente los algoritmos que hacen este trabajo están limitados identificando ciertas orientaciones causales como A — B — C, ya que la misma es equivalente en los siguientes tres casos A –> B –> C, A <– B –> C, A <– B <– C. Nuestro trabajo busca poder distinguir entre estos tres casos utilizando información de intervenciones llevadas a cabo por los investigadores y representadas como variables diferentes en los modelos, lo que nos permitirán orientar con certeza este tipo de relaciones causales.

Israel Dilán at Pittsburgh.