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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.

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:
What are popular job titles related to Weekend Machine Learning Postdoc jobs in Texas? For Weekend Machine Learning Postdoc jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Weekend Machine Learning Postdoc jobs in Texas look for? The top searched job categories for Weekend Machine Learning Postdoc jobs in Texas are:
What cities in Texas are hiring for Weekend Machine Learning Postdoc jobs? Cities in Texas with the most Weekend Machine Learning Postdoc job openings:
Weekend Machine Learning Postdoc jobs near you

IFML Postdoctoral Fellowship

The University of Texas at Austin

Austin, TX • On-site

$48.60K - $65.90K/yr

Full-time

Posted 15 days ago

University Of Texas at Austin rating

8.1

Company rating: 8.1 out of 10

Based on 62 frontline employees who took The Breakroom Quiz

128th of 529 rated colleges and universities

Job description

Description
The NSF AI Institute for Foundations of Machine Learning (IFML), and the NSF TRIPODS program at the University of Texas seek highly qualified candidates (within five years of the award of their PhD) for a new UT ML Research Fellow Program. Appointments will begin Summer or Fall 2024.
This multi-year program will host several postdoctoral researchers working on either:
(a) foundational problems in machine learning, optimization, and statistics and their relationship to algorithmic and methodological improvements for training and deploying ML models or
(b) problems that advance the state of the art in central use-cases of large scale ML: video, imaging, and navigation or some combination of the above topics or
(c) deep learning and protein biologics, especially protein engineering and applications of large-scale tools such as AlphaFold (we encourage candidates with PhDs in biology, chemistry, biochemistry or related fields with a background in computation to apply).
Descriptions of the scientific agendas of IFML and TRIPODS can be found at ifml.institute and ml.utexas.edu/tripods respectively.
A description of the IFML scientific agenda can be found at ifml.institute.
Fellows will be able to collaborate with numerous researchers and faculty involved in IFML partner institutions: the Machine Learning Lab at UT Austin, the University of Washington, Microsoft Research (Redmond), and Wichita State University. Fellows will play a leading role in organizing seminars, workshops and other research activities. The anticipated term for a fellowship is one or two years - to be decided at the time of appointment, with the possibility of extension based on mutual agreement. In addition to competitive salary and benefits, the fellowship also includes funding for independent travel to workshops, conferences and other universities and research labs.
Simultaneous applications for a joint Simons-UT ML Research Fellowship are possible! Please indicate a simultaneous application in your materials.
Application Instructions
Submission requirements: a CV, research statement, and two reference letters. Applications will be accepted and reviewed on a rolling basis.
Equal Employment Opportunity Statement
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.

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