Postdoctoral Fellow- Machine Learning...

Genentech
South San Francisco, CA, United States
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$110,000.0 - $120,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Encodings Computational Biology Machine Learning Information Technology

Requirements

  • Ph.D. with a proven track record of excellence in Computer Science and Machine Learning, with substantial domain experience in biology and genomics.

  • Must have advanced at least one key research project as evidenced by a first author paper published or accepted in a leading peer-reviewed journal.

  • You must have advanced technical training, as evidenced by a top method-focused conference or journal publication or sophisticated methods used as part of a biologically focused publication.

  • Independent scientist with outstanding communication skills, a strong passion and commitment to science and computational biology, who works well within a team.

  • Excited about developing and applying cutting-edge ML/AI models to solve open problems in genomics and biology.

Preferred Qualifications:

  • Experience with sequence-to-function modeling.

  • Working knowledge of public regulatory genomic resources and datasets, such as ENCODE, GTEx, etc.

About the company

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Genentech.

A Postdoctoral fellow position is available for a highly motivated and independent candidate to join the laboratory of Dr. Sara Mostafavi in the Department of Computational Sciences at Genentech. The group develops and applies state-of-the-art ML/AI models to address open questions in genome biology, with the goal of understanding causal mechanisms of disease and facilitating drug discovery. This position in particular focuses on sequence-to-function deep genomics modeling, with the goal of developing performant models that make generalizable out-of-distribution predictions, facilitating the understanding of causal relationships between genetic variation and disease outcomes.

The Opportunity:

  • You will be able to take advantage of in-house and world-renown expertise in regulatory genomics and core ML/AI modeling.

  • You will be able to interact and work in partnership with collaborators from very strong human genetics and cellular genomics departments.

  • You will be part of the Genentech post-doctoral training program that provides an outstanding environment and the opportunity to pursue fundamental basic science questions in an environment focused on drug development and breakthrough discoveries., Elevate your research career to new heights with Genetech’s Postdoctoral Program! Join a prestigious community of early career scientists and kick-start your journey toward becoming a scientific leader in biotechnology and bioengineering. With competitive salaries and fully funded research expenses, you can dedicate yourself to groundbreaking research that aligns with Genentech strategic ambitions.

The postdoc program is designed to empower recent Ph.D. graduates to conduct world-class research, publish in top-tier journals, and build a robust scientific network. By joining us, you will receive the mentorship and support necessary to develop into an independent scientist and leader.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.juju.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:19 min

Empowering life science researchers with artificial intelligence

Jeremy Murray Jeremy Murray · WWC Europe 2026

54 sec

Detecting smart devices and experimenting with biological computing networks

Chris Heilmann +2 · LIVE

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

3:17 min

Optimizing character encoding with Kim variable byte encoding

Douglas Crockford Douglas Crockford · WWC 2024

2:14 min

Advancing biocatalyst research through quantum machine learning algorithms

Alexandra Waldherr · LIVE

5:42 min

Evaluating bizarre tech headlines in fake or news segment

Chris Heilmann +2 · LIVE

Videos

See all

Related articles

See all