Machine Learning Research Scientist, ODL Brain Institute
DALLAS, TXPosted 30+ days ago
Job summary
Job post source
This job is directly from UT Southwestern Medical Center
Job overview
The Machine Learning Research Scientist at UT Southwestern Medical Center contributes to neuroscience research by studying neural networks in the brain, focusing on learning and memory, and supporting research on neurodegenerative disease models.
Responsibilities and impact
The role involves managing research projects, performing system administration, maintaining GPU computing resources, developing software for optical imaging data analysis, collaborating with interdisciplinary teams, and contributing to research publications.
Compensation and benefits
The position offers a competitive benefits package including PPO medical plan with no cost for employee-only coverage, paid time off from day one, retirement programs, paid parental leave, wellness programs, tuition reimbursement, and eligibility for Public Service Loan Forgiveness.
Experience and skills
Candidates should have a PhD, Master's, or Bachelor's degree in relevant fields with significant research experience; strong programming skills in Python, Linux administration, cloud computing, knowledge of machine learning techniques, and experience with electronics and imaging software are preferred.
Career development
UT Southwestern provides opportunities for career growth and development aligned with future goals, including attending conferences and co-authoring publications.
Work environment and culture
The company culture emphasizes teamwork, professionalism, innovation, and compassion within a world-renowned medical and research center environment.
Company information
UT Southwestern Medical Center is a leading medical and research institution in Dallas-Fort Worth with over 75 years of excellence, ranked number 1 hospital in the region by U.S. News & World Report.
Team overview
The candidate will join the Program for Memory Longevity led by Dr. Attila Losonczy, working in an interdisciplinary team focused on neural network research in the brain.
Job location and travel
The job is located at 5323 Harry Hines Blvd, Dallas, Texas, with a full-time day schedule.
Unique job features
This role uniquely combines expertise in machine learning, neuroscience, and custom electronics development to advance research on brain function and neurodegenerative diseases.
Company overview
UT Southwestern Medical Center is a leading academic medical institution located in Dallas, Texas, renowned for its cutting-edge research, exceptional patient care, and top-tier medical education. The center generates revenue through a combination of patient services, research grants, and educational programs. Established in 1943, it has grown to include multiple hospitals and research facilities, consistently ranking among the best in the nation for various specialties. Notable achievements include pioneering research in genetics, cancer, and neuroscience, making it a prestigious place for medical professionals and researchers.
How to land this job
Position your resume to highlight your expertise in machine learning, neural networks, and deep learning, emphasizing programming skills in Python and experience with Linux system administration and GPU computing relevant to brain research.
Focus on showcasing experience with data processing, software development for optical imaging analysis, and interdisciplinary collaboration, as these are key responsibilities in the role at UT Southwestern Medical Center.
Apply through multiple platforms including the UT Southwestern Medical Center career site, LinkedIn, and other job boards to maximize your application visibility and opportunities.
Connect with current researchers and staff in the ODL Brain Institute or the Program for Memory Longevity on LinkedIn, using ice breakers like commenting on recent publications from the team or expressing enthusiasm about their work on neural network organization and neurodegenerative disease models.
Optimize your resume for ATS by incorporating keywords from the job description such as 'deep learning,' 'Python programming,' 'GPU computing,' 'optical imaging analysis,' and 'Linux system administration' to ensure it passes automated screenings.
Utilize Jennie Johnson's Power Apply feature to automate tailored applications, find multiple application channels, and identify relevant LinkedIn contacts, allowing you to focus your time on preparing for interviews and networking effectively.
Jennie Johnson works for you!
Here’s what we do to make sure you’re successful:
Targeted Resume Revamp:
We expertly craft your resume to navigate Applicant Tracking Systems (ATS) and showcase your qualifications, making you stand out as a top-tier candidate.
Job Description Dissection:
Unpack the job posting with expert analysis, ensuring your application hits every key requirement.
Bespoke Cover Letter:
Capture the attention of hiring managers with a personalized cover letter that highlights how your skills align perfectly with the job's needs.
Interview Mastery:
Prepare for interviews like a pro with likely questions, strategic answers, and insightful questions for you to ask, setting you apart as an informed candidate.
Direct Application Insights:
Receive tailored advice on the best places to apply, ensuring your applications are seen by the right employers.
Skills and Gaps Assessment:
Identify and close critical skills gaps to position yourself as the best-fit candidate for your ideal job.
Personalized Email Pitch:
Make a memorable first impression with an email template crafted to engage potential employers and initiate meaningful conversations.
In-depth Research Guide:
Leverage comprehensive research tools to gather effective insights on companies, industry trends, and role-specific challenges.
Detailed Company Analysis:
Gain in-depth understanding of your prospective employer, giving you the edge in applications and interviews.
Strategic Candidate Overview:
Understand your unique value and why companies would want to interview you, highlighting your background and positioning.