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Summer Protein Engineering Jobs in Texas (NOW HIRING)

Summer Protein Engineering information

What is the difference between Summer Protein Engineering vs Summer Biochemical Engineering?

AspectSummer Protein EngineeringSummer Biochemical Engineering
Required CredentialsUndergraduate or Master's in Biochemistry, Molecular Biology, or related fieldsUndergraduate or Master's in Chemical Engineering, Biochemistry, or related fields
Work EnvironmentLaboratories focused on protein design, expression, and analysisLaboratories and process plants working on bioprocesses and fermentation
Industry UsagePharmaceuticals, biotech, research institutionsBiotech, pharmaceuticals, industrial bioprocessing

Summer Protein Engineering typically involves designing and modifying proteins in research labs, focusing on molecular techniques. In contrast, Summer Biochemical Engineering emphasizes developing bioprocesses and scaling up production. Both roles require strong backgrounds in biology and chemistry but differ in their specific applications and work environments.

What are the most commonly searched types of Protein Engineering jobs in Texas?

The most popular types of Protein Engineering jobs in Texas are:

What cities in Texas are hiring for Summer Protein Engineering jobs?

Cities in Texas with the most Summer Protein Engineering job openings:

IFML Postdoctoral Fellowship

Austin, TX • On-site


The University of Texas at Austin
Education • 10K+ employees

8.3

Company rating: 8.3 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

128th of 622 rated colleges and universities

People enjoy working here

Good employer

Recommended by students


$48K - $65K/yr

Full-time

Re-posted 11 days ago


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.


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