Hispanic Alliance for Career Enhancement
2026 Future Talent Program - Translational Genome Analytics, Computational Biolo
Hispanic Alliance for Career Enhancement, South San Francisco, California, us, 94083
Overview
The Future Talent Program features Cooperative (Co-op) education that lasts up to 6 months and includes one or more projects. These opportunities in our Research and Development Division can provide you with development experiences and help you evaluate long-term fit with our company.
The Future Talent Program within the Research and Development Data, AI, and Genome Sciences (DAGS) Department offers six-month co-op opportunities within the Translational Genome Analytics group. We have 2 positions at multiple US locations. Candidates may apply to participate in one or more of the computational biology projects listed below. These projects are designed to help students develop their skills and assess whether we are the right company for their long-term goals. We are seeking highly motivated and talented students with computational skills and experience.
Projects
Translational Genome Analytics (1 position, On Site in San Francisco, CA)
Develop interpretable AI/ML models and generate insights to delineate the mechanistic underpinnings of drug effects, and distribution effects across a heterogeneous population of tumor models, to enable data-driven inference of rational drug combinations.
Analyze large-scale anti-tumor drug and/or genetic perturbations and sensitivity screens with state-of-the-art machine learning methods to generate associations between background cellular contexts, transcriptional responses, and drug sensitivity/resistance.
Mine large-scale internal and external datasets (e.g. RNA-seq, single cell RNA-seq, ATAC-seq, DRUG-seq) with state-of-the-art methods to enable discovery of therapeutic targets and precision biomarkers in oncology.
Translational Genome Analytics (1 position, On Site in Cambridge MA)
Analyze large-scale Alzheimer's disease multi-omic datasets (e.g. WGS, RNA-seq, single cell RNA-seq, ATAC-seq) with state-of-the-art methods to decode disease-associated molecular alterations.
Fine-tune pre-trained transformer models using disease-specific multi-omic datasets to delineate co-regulated gene modules with the goal of distinguishing Alzheimer's disease-associated gene expression patterns at the bulk and/or single-cell level.
Evaluate the accuracy and utility of cutting-edge pre-trained AI/ML transformer models in imputing disease-related transcriptomic patterns to enable integration of sparse multi-omics disease datasets and drive discovery of therapeutic targets and/or patient stratification biomarkers in Alzheimer's disease.
Required Education and Skills
Candidates must be currently enrolled in a minimum of a Bachelor's degree program in Biomedical Engineering, Computer Science, Biological Sciences or a related field. Students enrolled in graduate programs (MS or PhD) are highly encouraged to apply.
Candidates must be available to work full-time for 6 months in 2026.
Candidates must have excellent academic achievement and strong data science abilities.
Candidates must have demonstrated superior communication and interpersonal skills and must be able to work well in a collaborative team environment.
Preferred Skills and Experience
Candidates should have interests/experience in oncology, immunology or neuroscience, with a strong emphasis on data science, AI/ML, computational biology and/or experience with large-scale molecular profiling data analyses.
For these computational projects, preferred skill sets include one or more of the following: experience with R or Python, basic biostatistics, analysis of bulk or single-cell datasets.
Please note : This position may be closed before the posted end date or may remain open longer, at the discretion of the company.
Additional Details Under New York City, Colorado State, Washington State, and California State law, the Company is required to provide a reasonable estimate of the salary range for this job. Final determinations with respect to salary will consider factors such as location, skills, experience, and education.
Salary range:
The salary range for this role is $39,600.00-$105,500.00 USD
Job Posting End Date:
11/3/2025
Employee Status:
Intern/Co-op (Fixed Term)
Relocation:
No relocation
VISA Sponsorship:
No
Travel Requirements:
No Travel Required
Shift:
Not Indicated
Required Skills:
(see Required Education and Skills above)
Preferred Skills:
(see Preferred Skills above)
Equal Employment Opportunity : Our company is an Equal Employment Opportunity Employer. We provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other legally protected characteristics. We comply with applicable laws and encourage a diverse and inclusive workplace.
Hybrid Work Model : U.S. hybrid work model guidance applies to eligible positions. Details vary by site and role.
Note : This description is intended to reflect the current job responsibilities and requirements and is subject to change at the company's discretion.
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The Future Talent Program within the Research and Development Data, AI, and Genome Sciences (DAGS) Department offers six-month co-op opportunities within the Translational Genome Analytics group. We have 2 positions at multiple US locations. Candidates may apply to participate in one or more of the computational biology projects listed below. These projects are designed to help students develop their skills and assess whether we are the right company for their long-term goals. We are seeking highly motivated and talented students with computational skills and experience.
Projects
Translational Genome Analytics (1 position, On Site in San Francisco, CA)
Develop interpretable AI/ML models and generate insights to delineate the mechanistic underpinnings of drug effects, and distribution effects across a heterogeneous population of tumor models, to enable data-driven inference of rational drug combinations.
Analyze large-scale anti-tumor drug and/or genetic perturbations and sensitivity screens with state-of-the-art machine learning methods to generate associations between background cellular contexts, transcriptional responses, and drug sensitivity/resistance.
Mine large-scale internal and external datasets (e.g. RNA-seq, single cell RNA-seq, ATAC-seq, DRUG-seq) with state-of-the-art methods to enable discovery of therapeutic targets and precision biomarkers in oncology.
Translational Genome Analytics (1 position, On Site in Cambridge MA)
Analyze large-scale Alzheimer's disease multi-omic datasets (e.g. WGS, RNA-seq, single cell RNA-seq, ATAC-seq) with state-of-the-art methods to decode disease-associated molecular alterations.
Fine-tune pre-trained transformer models using disease-specific multi-omic datasets to delineate co-regulated gene modules with the goal of distinguishing Alzheimer's disease-associated gene expression patterns at the bulk and/or single-cell level.
Evaluate the accuracy and utility of cutting-edge pre-trained AI/ML transformer models in imputing disease-related transcriptomic patterns to enable integration of sparse multi-omics disease datasets and drive discovery of therapeutic targets and/or patient stratification biomarkers in Alzheimer's disease.
Required Education and Skills
Candidates must be currently enrolled in a minimum of a Bachelor's degree program in Biomedical Engineering, Computer Science, Biological Sciences or a related field. Students enrolled in graduate programs (MS or PhD) are highly encouraged to apply.
Candidates must be available to work full-time for 6 months in 2026.
Candidates must have excellent academic achievement and strong data science abilities.
Candidates must have demonstrated superior communication and interpersonal skills and must be able to work well in a collaborative team environment.
Preferred Skills and Experience
Candidates should have interests/experience in oncology, immunology or neuroscience, with a strong emphasis on data science, AI/ML, computational biology and/or experience with large-scale molecular profiling data analyses.
For these computational projects, preferred skill sets include one or more of the following: experience with R or Python, basic biostatistics, analysis of bulk or single-cell datasets.
Please note : This position may be closed before the posted end date or may remain open longer, at the discretion of the company.
Additional Details Under New York City, Colorado State, Washington State, and California State law, the Company is required to provide a reasonable estimate of the salary range for this job. Final determinations with respect to salary will consider factors such as location, skills, experience, and education.
Salary range:
The salary range for this role is $39,600.00-$105,500.00 USD
Job Posting End Date:
11/3/2025
Employee Status:
Intern/Co-op (Fixed Term)
Relocation:
No relocation
VISA Sponsorship:
No
Travel Requirements:
No Travel Required
Shift:
Not Indicated
Required Skills:
(see Required Education and Skills above)
Preferred Skills:
(see Preferred Skills above)
Equal Employment Opportunity : Our company is an Equal Employment Opportunity Employer. We provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other legally protected characteristics. We comply with applicable laws and encourage a diverse and inclusive workplace.
Hybrid Work Model : U.S. hybrid work model guidance applies to eligible positions. Details vary by site and role.
Note : This description is intended to reflect the current job responsibilities and requirements and is subject to change at the company's discretion.
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