The Singh Lab – Junior/Assistant/Associate/Full Specialist, Machine Learning and Aging

Position Description

The Singh Lab – Junior/Assistant/Associate/Full Specialist in Genomics, Machine Learning and Aging

SCHOOL OF MEDICINE – Department of Anatomy

Description

The Singh Lab at UCSF ( www.singhlabucsf.org ) is seeking a highly motivated Junior/Assistant/Associate/Full Specialist to join our research program at the intersection of aging biology, genomics, and machine learning. Our lab is tackling the fundamental questions in the field of aging using a multi-disciplinary approach. We integrate cutting-edge single-cell RNA sequencing (scRNA-seq) and other multi-omics datasets with advanced machine learning techniques to decipher the intricate genomic changes that drive aging and age-related diseases. We not only work with human and mouse data – we're also exploring the remarkable biology of the African killifish, a powerful model organism for aging research. By comparing genomic patterns across species, we aim to identify conserved processes that underlie aging and develop innovative strategies to promote healthy lifespan.

As a Junior/Assistant/Associate/Full Specialist In Our Lab, You Will

• Spearhead the development and application of novel AI/ML algorithms to analyze large-scale scRNA-seq datasets related to aging.
• Uncover hidden patterns and predict age-related changes and 'aging clocks' at the single-cell level.
• Identify key genes, pathways, and cell types that contribute to aging and age-related diseases.
• Collaborate with a dynamic team of researchers with multi-disciplinary expertise in genomics, bioinformatics, and aging biology.
• Contribute to a vibrant research community at UCSF, including the Bakar Aging Research Institute (BARI) and the Bakar Computational Health Sciences Institute (BCHSI).
  
  

Required Qualifications

• Must have (or be in process of obtaining) a bachelor’s degree (or equivalent degree) or four years of research experience to be appointed at the Junior rank.
• Must have (or be in process of obtaining) a master’s degree (or equivalent degree) or a bachelor's degree with three or more years of research experience to be appointed at the Assistant rank.
• Must have (or be in process of obtaining) a master's degree (or equivalent degree) five to ten years of research experience to be appointed at the Associate rank.
• Must have (or be in process of obtaining) a terminal degree (or equivalent degree) or at least ten or more years of research experience to be appointed at the Full rank.
  
  

Preferred Qualification

• Proven experience analyzing scRNA-seq, scATAC-seq or spatial-RNA-seq data.
• Proven experience expertise in AI/ML applied to genomic data.
• Proficiency in Python and relevant libraries for machine learning (e.g., scikit-learn, TensorFlow, PyTorch).
  
  

We will consider applications on a rolling basis until all positions are filled. We are seeking at least a 2-year commitment. Applicants must meet requirements by the time of the appointment.

Please apply online at https://aprecruit.ucsf.edu/JPF05498

See Table 24B for the salary range for this position. A reasonable estimate for this position is $53,100-$188,200.

Job location

San Francisco, CA

Requirements

Documents

Curriculum Vitae - Your most recently updated C.V.

Cover Letter (Optional)

Statement of Research (Optional)

Statement of Teaching (Optional)

Statement of Contributions to Diversity (Optional)

Misc / Additional (Optional)

References

2 references required (contact information only)

Document Requirements

• Curriculum Vitae - CV must clearly list current and/or pending qualifications (e.g. board eligibility/certification, medical licensure, etc.).
• Cover Letter (Optional)
• Statement of Research (Optional)
• Statement of Teaching (Optional)
• Statement of Contributions to Diversity - Please see the following page for more details: Contributions to Diversity Statement (Optional)
• Misc / Additional (Optional)
  
  

Reference Requirements

• 2 required (contact information only)
  
  

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. 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.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

• “Misconduct” means any violation of the policies or laws governing conduct at the applicant’s previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer.
• UC Sexual Violence and Sexual Harassment Policy: https://policy.ucop.edu/doc/4000385/SVSH
• UC Anti-Discrimination Policy for Employees, Students and Third Parties: https://policy.ucop.edu/doc/1001004/Anti-Discrimination
• APM - 035: Affirmative Action and Nondiscrimination in Employment: https://www.ucop.edu/academic-personnel-programs/_files/apm/apm-035.pdf
  
  

San Francisco, CA