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Weekend Machine Learning Postdoc Jobs (NOW HIRING)

Freenome

Senior Machine Learning Scientist

Brisbane, CA · On-site

$110.10K - $150.40K/yr

... postdoc or post-PhD industry experience achieving impactful results using relevant modeling ... machine learning, deep learning and complex data modeling. * Practical and theoretical ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199.68K - $283.50K/yr

... postdoc or post-PhD industry experience achieving impactful results using relevant modeling ... machine learning, deep learning and complex data modeling. * Practical and theoretical ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199.68K - $283.50K/yr

... postdoc or post-PhD industry experience achieving impactful results using relevant modeling ... machine learning, deep learning and complex data modeling. * Practical and theoretical ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site

$199.68K - $283.50K/yr

... postdoc or post-PhD industry experience achieving impactful results using relevant modeling ... machine learning, deep learning and complex data modeling. * Practical and theoretical ...

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Weekend Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive as a Weekend Machine Learning Postdoc, and why are they important?

To thrive as a Weekend Machine Learning Postdoc, you need a strong background in machine learning, statistics, and programming, typically supported by a PhD in a relevant field. Experience with tools such as Python, TensorFlow, PyTorch, and data analysis platforms, as well as familiarity with academic research methodologies, is essential. Exceptional problem-solving abilities, self-motivation, and effective communication are vital soft skills for success in research and collaboration. These skills enable you to drive innovative research, efficiently manage independent projects, and contribute meaningful insights to the field.

What are the typical projects and collaboration opportunities for a Weekend Machine Learning Postdoc?

As a Weekend Machine Learning Postdoc, you will often contribute to ongoing research projects, developing and refining machine learning models in collaboration with faculty, graduate students, and occasionally industry partners. While your hours are concentrated on weekends, you’ll typically participate in regular research meetings, code reviews, and may co-author papers or grant proposals. The role provides opportunities to mentor junior researchers and expand your expertise by working on interdisciplinary teams. This structure allows you to make significant research contributions while maintaining flexibility in your schedule.

What is a Weekend Machine Learning Postdoc?

A Weekend Machine Learning Postdoc is a postdoctoral researcher who focuses on machine learning projects and typically works on weekends or has a flexible schedule that includes weekend hours. This role often involves conducting advanced research in machine learning, developing algorithms, publishing papers, and collaborating with academic or industry teams. Weekend postdoc positions may be ideal for those balancing other commitments or seeking non-traditional work hours while continuing their research careers.

What is the difference between Weekend Machine Learning Postdoc vs Weekend Data Scientist?

AspectWeekend Machine Learning PostdocWeekend Data Scientist
Required CredentialsPhD in Computer Science, Machine Learning, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentAcademic research settings, universities, research labsIndustry companies, startups, consulting firms
Employer & Industry UsageResearch institutions, universities, academic grantsTech companies, finance, healthcare, retail
Common Search & ComparisonYesYes

The Weekend Machine Learning Postdoc typically involves academic research with a focus on advancing machine learning theories and models, often requiring a PhD. In contrast, a Weekend Data Scientist applies data analysis and machine learning techniques in industry settings, often with a bachelor's or master's degree. Both roles may work on similar projects but differ mainly in their environment, credentials, and end goals.

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Weekend Machine Learning Postdoc jobs near you
Senior Machine Learning Scientist

Senior Machine Learning Scientist

Freenome

Brisbane, CA • On-site

$110.10K - $150.40K/yr

Full-time

Posted 12 days ago

Job description

About this opportunity:
At Freenome, we are seeking a Senior Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, and the ability to thrive in a highly cross-functional environment.
They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.
The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.
What you'll do:
  • Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
  • Build new models or fine-tune existing models to identify biological changes resulting from disease.
  • Build models that achieve high accuracy and that generalize robustly to new data.
  • Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
  • Work closely with ML Engineering partners to ensure that Freenome's computational infrastructure supports optimal model training and iteration.
  • Take a mindful, transparent, and humane approach to your work.

Must haves:
  • PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
  • 3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
  • Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modeling.
  • Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks.
  • Practical and theoretical understanding of DL models like large language models or other foundation models.
  • Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
  • Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
  • Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
  • Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
  • Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
  • Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
  • A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:
  • Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
  • Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
  • Experience in NGS data analysis and bioinformatic pipelines.
  • Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
  • Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.

Benefits and additional information:
The US target range of our base salary/hourly rate for new hires is $173,775 - $246,750. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered. Please note that individual total compensation for this position will be determined at the Company's sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.
Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.
Applicants have rights under Federal Employment Laws.
  • Family & Medical Leave Act (FMLA)
  • Equal Employment Opportunity (EEO)
  • Employee Polygraph Protection Act (EPPA)

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