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Weekend Machine Learning Postdoc Jobs in Texas (NOW HIRING)

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Weekend Machine Learning Postdoc information

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.

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 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 most commonly searched types of Machine Learning Postdoc jobs in Texas? The most popular types of Machine Learning Postdoc jobs in Texas are:
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Weekend Machine Learning Postdoc jobs near you
Postdoctoral Associate - Clinical Bioinformatics

Postdoctoral Associate - Clinical Bioinformatics

Baylor College of Medicine

Houston, TX • On-site

Full-time

Posted 3 days ago

Baylor College of Medicine rating

8.6

Company rating: 8.6 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

52nd of 538 rated colleges and universities

Job description

Job Summary:
Baylor College of Medicine is seeking a Postdoctoral Associate to collaborate on innovative projects that integrate patient-level data with artificial intelligence and machine learning methodologies. The role involves developing algorithms, annotating clinical data, and collaborating with various teams to enhance patient care through clinical informatics.
Responsibilities:
• Collaborates on the development of AI/ML/NLP-driven solutions for healthcare challenges.
• Reads and interprets patient-level data to support the development of AI/ML/NLP algorithms for clinical applications.
• Annotates medical notes and datasets to facilitate training and validation of predictive models.
• Collaborates with data scientists, machine learning engineers, and clinical collaborators to design, implement, and validate innovative algorithms.
• Conducts exploratory data analysis to extract meaningful insights from complex datasets.
• Writes manuscripts and prepare presentations for local, national, and international conferences.
• Conducts literature reviews and maintains awareness of advancements in bioinformatics, AI, and clinical data analysis.
• Applies foundational knowledge of biostatistics and AI principles to inform study design and algorithm development.
• Tests, debugs, and validates models in partnership with technical and clinical teams.
• Ensures adherence to ethical guidelines for the use of patient data in research and development.
• Works closely with the Artificial Intelligence in Health Lab (AIH-Lab) and the BD-STEP program to advance clinical informatics research.
• Leverages clinical expertise to refine machine learning models, ensuring clinical relevance and accuracy.
• Collaborates on the integration of clinical datasets into broader health informatics systems.
• Provides expert annotations for training large language models (LLMs) and NLP algorithms, focusing on healthcare-specific use cases.
• Presents findings in department meetings and seminars and support grant writing and funding initiatives.
• Mentors trainees or junior team members in clinical informatics and research methods as needed.
• Performs other job-related duties as assigned.
Qualifications:
Required:
• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.
Preferred:
• MD passionate about clinical bioinformatics and driving innovation in healthcare.
• Able to write manuscripts, present research findings locally and nationally, and contribute to advancing clinical informatics.
• Background in basics statics.
• Background in basics AI.
Company:
Baylor College of Medicine, located in the Texas Medical Center, is a health sciences university located in Houston, Texas Founded in 1900, the company is headquartered in Houston, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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