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Federated Learning Phd Jobs (NOW HIRING)

PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field ... Familiarity with differential privacy, federated learning, and secure multi-party computation

Master's or PhD in Machine Learning, Computer Science, AI, or a related field * Experience with ... Familiarity with privacy-preserving ML techniques such as federated learning * Experience ...

Sr. Director Data & AI Platforms

Atlanta, GA

$64.75 - $86.50/hr

MS or PhD in Computer Science, Machine Learning, Data Engineering, or a related field - or ... federated learning, model watermarking, adversarial robustness patterns, and AI-specific access ...

Master's or PhD in Machine Learning, Computer Science, AI, Mathematics, or related field * Experience with privacy-preserving AI such as federated learning or secure execution * Strong mathematical ...

Sr. Director Data & AI Platforms

Atlanta, GA · On-site

$64.75 - $86.50/hr

MS or PhD in Computer Science, Machine Learning, Data Engineering, or a related field - or ... federated learning, model watermarking, adversarial robustness patterns, and AI-specific access ...

PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field ... Familiarity with differential privacy, federated learning, and secure multi-party computation

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Federated Learning Phd information

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$13

$32

$56

How much do federated learning phd jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for federated learning phd in the United States is $32.69, according to ZipRecruiter salary data. Most workers in this role earn between $21.63 and $43.27 per hour, depending on experience, location, and employer.

What are some common challenges faced by a Federated Learning PhD in collaborative research environments?

As a Federated Learning PhD, you'll often work at the intersection of machine learning, privacy, and distributed systems, collaborating with interdisciplinary teams. A key challenge is addressing data heterogeneity and ensuring model robustness across diverse, decentralized datasets. Coordinating experiments across multiple organizations or devices while maintaining privacy and security can be complex. Effective communication and project management skills are essential to align research goals and integrate feedback from collaborators in academia or industry.

What is the difference between Federated Learning Phd vs Data Scientist?

AspectFederated Learning PhdData Scientist
Required CredentialsPhD in Computer Science, Machine Learning, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch-focused, often in academia or R&D departmentsIndustry settings, analytics teams, product development
Industry UsageSpecialized research projects, AI development, privacy-preserving MLData analysis, modeling, business insights, product optimization

Federated Learning Phds typically focus on advanced research in privacy-preserving machine learning, requiring a PhD and a strong background in AI. Data Scientists work across industries analyzing data to inform business decisions, often with a Bachelor's or Master's degree. While both roles involve machine learning, Federated Learning Phds are more research-oriented, whereas Data Scientists focus on applied data analysis.

What are the key skills and qualifications needed to thrive as a Federated Learning PhD, and why are they important?

To thrive as a Federated Learning PhD, you need deep expertise in machine learning, distributed systems, and data privacy, typically supported by a PhD in computer science or related fields. Proficiency with Python, TensorFlow, PyTorch, and specialized federated learning frameworks, as well as knowledge of secure aggregation and privacy-enhancing technologies, is essential. Strong research, problem-solving, and communication skills help you navigate complex challenges and collaborate effectively in academia or industry. These skills ensure the ability to advance federated learning techniques and deliver scalable, privacy-preserving AI solutions.

What is a Federated Learning PhD?

A Federated Learning PhD refers to a doctoral research position or program focused on federated learning, a machine learning approach where models are trained collaboratively across multiple devices or servers while keeping the underlying data decentralized and private. This research typically explores new algorithms, privacy-preserving techniques, system architectures, and applications of federated learning in fields like healthcare, finance, and edge computing. A PhD in this area involves both theoretical study and practical experiments, preparing graduates for advanced roles in academia or industry related to privacy-aware artificial intelligence.
Director/Senior Director, ADMET & PK/PD Modeling

Director/Senior Director, ADMET & PK/PD Modeling

Lilly

Boston, MA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 hours ago


Eli Lilly and Company rating

8.8

Company rating: 8.8 out of 10

Based on 62 frontline employees who took The Breakroom Quiz

11th of 71 rated pharmaceutical


Job description

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We're looking for people who are determined to make life better for people around the world.

OrganizationOverview

Lilly Catalyze360 isacomprehensive approach to enabling the early-stage biotech ecosystem by democratizing access to infrastructure,expertise, and resources. Through its interconnected pillars-Lilly Ventures, Lilly Gateway Labs, LillyExploR&D, and LillyTuneLab-Catalyze360 strategically removes barriers that traditionally block bold science from becoming life-changingmedicines, providingbiotechswith flexible combinations of capital, physical lab space, R&D capabilities, AI/ML tools, and decades of enterprise learning.

LillyTuneLabisan artificial intelligence and machine learning (AI/ML) platform that provides biotech companies access to drug discovery models trainedonyears of Lilly's research data. Lilly estimates that this first release of AI models includes proprietary data obtained at a cost of over$1 billion,representingone of the industry's most valuable datasets used to train an AI system available to biotechnology companies.By integrating advanced in silico modelling and federated learning, we connect pioneering machine learning algorithms, substantial computational power, exclusive datasets, and Lilly's domain-specific knowledge to drive innovation in drug discovery andfacilitateaccess tooptimaltherapies for patients.

Responsibilities

Model Development: Build and validate predictive models across key ADMET and PK/PD endpoints - including clearance, permeability, solubility, metabolic stability, DDI risk, transporter liabilities, exposure-toxicity relationships, and PK/PD - grounded in mechanistic understanding and designed for partner use.

Translational Modeling: Develop translational modeling approaches - including PBPK, IVIVE, and PK/PD simulation - to bridge preclinical and clinical settings and generate actionable predictions for biotech partners across diverse programs and modalities.

Distribution Modeling: Develop mechanistic and data-driven models for tissue distribution, volume of distribution, plasma protein binding, and blood-brain barrier penetration. Ensure models are calibrated across relevant species and translatable to human predictions.

Partner Enablement & Usability: Translate complex ADMET and PK/PD science into practical, interpretable model outputs and workflows. Develop clear documentation, decision frameworks, and companion guidance that make TuneLab's tools usable by partner teams with varying levels of quantitative expertise.

Data Strategy & Validation: Define data requirements and validation approaches to ensure models are scientifically sound, reproducible, and fit for purpose. Identify training data gaps and collaborate with internal teams to address them through targeted experimental or modeling initiatives.

AI & Tool Integration: Leverage AI and agentic tools to automate data pipelines, improve model interpretability, and streamline delivery of outputs to partners across TuneLab's federated network.

Mentorship: Provide coaching to junior scientists and contribute to TuneLab's growing ADMET and PK/PD modeling capabilities.

Basic Qualifications
  • Education: PhD in Pharmaceutical Sciences, Pharmacokinetics, Pharmacometrics, Clinical Pharmacology, Drug Metabolism, Toxicology, or a related STEM discipline.
  • Experience: 7+ years of relevant experience in ADME/PKPD, Pharmacometrics, Translational Medicine, or a closely related field.
Additional Skills/Preferences
  • Hands on experience with modelling platforms used in relevant fields such as SimCYP, GastroPlus, PK-Sim, NONMEM, Monolix, R, Matlab etc.
  • Extensive knowledge of medicinal chemistry and/or toxicology principles
  • Experience with small molecule discovery, including Beyond-Rule-of-Five and pan-modality chemotypes.
  • Strong communication skills with the ability to make complex quantitative science accessible to diverse audiences.
  • Track record of scientific contributions to pharmacokinetics, pharmacodynamics, ADMET, or pharmaceutical sciences.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.


Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women's Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.

Actual compensation will depend on a candidate's education, experience, skills, and geographic location. The anticipated wage for this position is

$177,000 - $308,000

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly's compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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About Eli Lilly

Sourced by ZipRecruiter

Eli Lilly, based in Indianapolis, IN, US, is one of the pioneers in the pharmaceutical industry with a rich history dating back to 1876. This global pharmaceutical company focuses on discovering, developing, manufacturing and selling pharmaceutical products in approximately 120 countries. The company's product categories include endocrinology, oncology, cardiovascular, neuroscience, and immunology. Having invested over $9 billion in research and development in the past decade, Eli Lilly is also committed to creating high-quality medicines that meet real needs. As a recipient of several awards and recognitions, Eli Lilly is known for its focus on life-saving research and drug development. Their mission is to make medicines that help people live longer, healthier, and more active lives.

Industry

Pharmaceutical product wholesalers

Company size

10,000+ Employees

Headquarters location

Indianapolis, IN, US

Year founded

1876