What are the responsibilities and job description for the College Student - Epigenet & Molecular Carcinogenesis position at MD Anderson Cancer Center and Careers?
The Ishak laboratory at the MD Anderson Cancer Center seeks undergraduate students interested in contributing to our efforts to learn and develop computational approaches to analyze spatial single cell RNA-sequencing datasets from patient-derived premalignant tissues. This position is an uncompensated internship. Students will work directly under the guidance of a lab mentor to eventually gain project independence.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
Student will work with a lab mentor to develop approaches to quantify transcript abundance in single cells from spatial scRNA-seq data of
patient-derived premalignant tissues. Students will work directly under the guidance of a lab mentor to eventually gain project independence.
ELIGIBILITY REQUIREMENTS
Applicants must be currently enrolled in an undergraduate program. This position requires a strong background in computer science and biology, preferably exemplified with a research portfolio available for review on public repositories (such as Github). Students experienced in machine learning, artificial intelligence, and spatial scRNA-seq be most competitive. Students must be able to work on-site at the MD Anderson Cancer Center and commit 20 hours per week during standard work hours from 8am - 5pm.
Skills required:
I. Coding:
o Must be proficient in Python and Linux (Bash)
o Must be able to code without using AI assisted tools such as
ChatGPT
II. Fit / compatibility:
o Studious with commitment to scientific integrity
o Exhibit strong and independent problem-solving skills
III. Time commitment:
o Commit to work 20 hr / week on-site
o Work on-site during daytime hours (8:00 - 17:00)
o Meet at least once / week to discuss progress
Skills preferred:
ADDITIONAL APPLICATION INFORMATION
Learn more about our laboratory here: https://www.mdanderson.org/research/departments-labsinstitutes/labs/ishak-laboratory.html
POSITION INFORMATION
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
Student will work with a lab mentor to develop approaches to quantify transcript abundance in single cells from spatial scRNA-seq data of
patient-derived premalignant tissues. Students will work directly under the guidance of a lab mentor to eventually gain project independence.
ELIGIBILITY REQUIREMENTS
Applicants must be currently enrolled in an undergraduate program. This position requires a strong background in computer science and biology, preferably exemplified with a research portfolio available for review on public repositories (such as Github). Students experienced in machine learning, artificial intelligence, and spatial scRNA-seq be most competitive. Students must be able to work on-site at the MD Anderson Cancer Center and commit 20 hours per week during standard work hours from 8am - 5pm.
Skills required:
I. Coding:
o Must be proficient in Python and Linux (Bash)
o Must be able to code without using AI assisted tools such as
ChatGPT
II. Fit / compatibility:
o Studious with commitment to scientific integrity
o Exhibit strong and independent problem-solving skills
III. Time commitment:
o Commit to work 20 hr / week on-site
o Work on-site during daytime hours (8:00 - 17:00)
o Meet at least once / week to discuss progress
Skills preferred:
- Experience with high performance clusters (HPC)
- Experience with Kubernetes
- Experience using GPU
- Familiarity with Docker
- Familiar with machine learning algorithms and deep learning
- Experience with R
ADDITIONAL APPLICATION INFORMATION
Learn more about our laboratory here: https://www.mdanderson.org/research/departments-labsinstitutes/labs/ishak-laboratory.html
POSITION INFORMATION
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html
FACULTY MENTOR
Charles Ishak, PHD