1

Freelance Bioinformatics Machine Learning Jobs in Tennessee

Freelance Bioinformatics Machine Learning information

What are the key skills and qualifications needed to thrive as a Freelance Bioinformatics Machine Learning Specialist, and why are they important?

To thrive as a Freelance Bioinformatics Machine Learning Specialist, you need a strong background in biology, statistics, and programming (such as Python or R), typically supported by a relevant degree in bioinformatics, computer science, or a related field. Familiarity with bioinformatics tools (e.g., BLAST, Bioconductor), machine learning libraries (scikit-learn, TensorFlow), and experience with cloud computing platforms are highly valuable. Strong problem-solving, communication, and project management skills help distinguish top freelancers in this field. These capabilities are crucial for independently delivering accurate, actionable biological insights to clients and efficiently managing multiple projects.

What are some common challenges freelance bioinformatics machine learning professionals face when working with multiple clients?

Freelance bioinformatics machine learning professionals often encounter challenges such as managing diverse data formats, aligning project expectations, and ensuring data privacy across multiple clients. Each client may have unique datasets, varying levels of documentation, and different computational infrastructure, requiring adaptability and strong communication skills. Balancing multiple deadlines and maintaining clear, consistent reporting are also important to foster trust and long-term collaborations.

What does a Freelance Bioinformatics Machine Learning specialist do?

A Freelance Bioinformatics Machine Learning specialist applies machine learning techniques to analyze biological data, such as genomics, proteomics, and medical records, on a project-by-project basis. They typically work independently with research labs, biotech companies, or healthcare organizations to develop algorithms, build predictive models, and interpret complex biological datasets. Their work helps drive insights in areas like drug discovery, personalized medicine, and disease prediction, often leveraging tools like Python, R, and specialized bioinformatics software. As freelancers, they have the flexibility to choose projects, set their schedules, and work remotely.

What is the difference between Freelance Bioinformatics Machine Learning vs Freelance Data Scientist?

AspectFreelance Bioinformatics Machine LearningFreelance Data Scientist
CredentialsBackground in bioinformatics, biology, or related fields; knowledge of machine learningBackground in statistics, computer science, or related fields; strong programming skills
Work EnvironmentResearch labs, biotech companies, academic projects, freelance consultingVarious industries including finance, tech, healthcare, consulting
Industry UsagePrimarily biotech, healthcare, genomics, pharmaceutical sectorsBroad industry application including finance, marketing, tech, healthcare

Freelance Bioinformatics Machine Learning specialists focus on applying machine learning techniques to biological data, often working within biotech and healthcare sectors. In contrast, Freelance Data Scientists have a broader scope, working across multiple industries with diverse datasets. Both roles require strong analytical skills and programming expertise, but their industry focus and domain knowledge differ significantly.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Tennessee? The most popular types of Bioinformatics Machine Learning jobs in Tennessee are:
What are popular job titles related to Freelance Bioinformatics Machine Learning jobs in Tennessee? For Freelance Bioinformatics Machine Learning jobs in Tennessee, the most frequently searched job titles are:
What cities in Tennessee are hiring for Freelance Bioinformatics Machine Learning jobs? Cities in Tennessee with the most Freelance Bioinformatics Machine Learning job openings:
Postdoctoral Research Associate, Atomistic Simulations & AI-Driven Molecular Modeling

Postdoctoral Research Associate, Atomistic Simulations & AI-Driven Molecular Modeling

Oak Ridge National Laboratory

Oak Ridge, TN • On-site

Full-time

Posted 19 days ago


Oak Ridge National Laboratory rating

9.3

Company rating: 9.3 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

4th of 103 rated laboratories


Job description

Job Summary:
Oak Ridge National Laboratory (ORNL) is seeking a motivated Postdoctoral Research Associate to focus on large-scale molecular dynamics simulations and AI-integrated multiscale modeling of complex biosystems. The successful candidate will work at the intersection of high-performance computing, computational biophysics, and machine learning, contributing to interdisciplinary research and collaboration efforts across various teams.
Responsibilities:
• Develop and apply scalable molecular dynamics (MD) and multiscale simulation workflows for biomolecular systems (proteins, enzymes, membranes, and complexes)
• Integrate AI/ML approaches with physics-based simulations to accelerate discovery and improve predictive fidelity
• Contribute to cross-scale modeling frameworks linking molecular interactions to cellular and network-level behavior (e.g. protein-protein interaction, PPI, network analysis)
• Optimize simulation codes and workflows for leadership-class HPC architectures
• Collaborate across interdisciplinary teams spanning biology, chemistry, computer science, and applied mathematics
• Publish findings in high-impact journals and present at leading conferences
Qualifications:
Required:
• Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field
• Strong programming skills in C++, Python, or similar scientific computing languages
• Hands-on experience with MD simulation tools such as NAMD, GROMACS, AMBER, or LAMMPS, and visualization tools (e.g., VMD, PyMOL)
• Experience working on high-performance computing (HPC) systems
• Demonstrated ability to conduct independent research with a good publication record
• Excellent written and verbal communication skills for interdisciplinary collaboration
• Commitment to ORNL’s core values: Impact, Integrity, Teamwork, Safety, and Service
Preferred:
• Deep expertise in atomistic and multiscale simulation methods (e.g., MD, enhanced sampling, QM/MM)
• Experience improving performance and scalability of simulation workflows via: Parallelization and performance engineering, GPU/accelerator optimization, Algorithmic innovation
• Experience applying machine learning or AI to molecular simulation, including: Surrogate models or learned potentials, Generative models for biomolecular design, Representation learning for biomolecular systems
• Familiarity with protein–protein interaction (PPI) networks, signaling pathways, or systems biology models (bioinformatics tools and models)
• Experience with integrated multiscale modeling frameworks connecting molecular dynamics to cellular or tissue-scale processes
• Experience with deep learning frameworks such as PyTorch or TensorFlow
• Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving foundation models or scientific LLMs
Company:
Oak Ridge National Laboratory holds a range of R&D assignments, from fundamental nuclear physics to applied R&D on advanced energy systems. Founded in 1943, the company is headquartered in Oak Ridge, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

What Oak Ridge National Laboratory employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom