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Postdoctoral Position Cognitive Neuroscience Jobs in Indiana

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Postdoctoral Position Cognitive Neuroscience information

What is a postdoctoral position in cognitive neuroscience?

A Postdoctoral Position in Cognitive Neuroscience is a temporary research role for individuals who have recently completed their PhD in neuroscience or a related field. These positions allow researchers to deepen their expertise, conduct independent or collaborative studies, and publish scientific findings on topics like brain function, cognition, and behavior. Postdocs often work in university labs, collaborate with interdisciplinary teams, and may also mentor students. The experience gained in these roles is essential for pursuing academic faculty positions or advanced research careers in neuroscience.

What are the typical research and collaboration opportunities for a postdoctoral researcher in cognitive neuroscience?

As a postdoctoral researcher in cognitive neuroscience, you will often engage in both independent and collaborative research projects, frequently working alongside faculty, graduate students, and interdisciplinary teams. Your daily activities may include designing experiments, analyzing neuroimaging or behavioral data, and preparing manuscripts for publication. Collaboration with other labs, both within your institution and externally, is common and can open doors to co-authored publications and grant funding opportunities. Participation in lab meetings, journal clubs, and conferences is also typical, helping you stay connected with the latest developments and network within the scientific community.

What are the key skills and qualifications needed to thrive as a postdoctoral researcher in cognitive neuroscience, and why are they important?

To thrive as a Postdoctoral Researcher in Cognitive Neuroscience, you typically need a PhD in neuroscience, psychology, or a related field, along with a solid background in experimental design and statistical analysis. Familiarity with neuroimaging tools (e.g., fMRI, EEG), programming languages (such as Python or MATLAB), and data analysis software is crucial. Strong problem-solving, collaboration, and scientific communication skills help you excel in multidisciplinary research environments. These competencies enable rigorous research, effective teamwork, and the advancement of knowledge in cognitive neuroscience.

What are popular job titles related to Postdoctoral Position Cognitive Neuroscience jobs in Indiana?

For Postdoctoral Position Cognitive Neuroscience jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Postdoctoral Position Cognitive Neuroscience jobs in Indiana look for?

The top searched job categories for Postdoctoral Position Cognitive Neuroscience jobs in Indiana are:

What cities in Indiana are hiring for Postdoctoral Position Cognitive Neuroscience jobs?

Cities in Indiana with the most Postdoctoral Position Cognitive Neuroscience job openings:

Advisor - Agent Research

Indianapolis, IN

Eli Lilly and Company
Pharmaceutical Product Wholesalers • 10K+ employees

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted yesterday


Eli Lilly and Company rating

8.9

Company rating: 8.9 out of 10

Based on 64 frontline employees who took The Breakroom Quiz


Job description

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work-but it's work worth doing. If you're driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.


Organization Overview

Lilly Small Molecule Discovery is an organization purpose-built to create molecules that make life better for people. We focus on using cutting edge science to unlock new approaches that can treat people suffering from diseases with poor treatment options. We continually challenge ourselves to deliver molecules that can provide breakthrough efficacy with the highest possible safety margins. We are dedicated to optimizing our mindset, technology, and processes for faster, more nimble execution. Our success is built on a culture that empowers innovative problem solving through open collaboration and individual accountability.

Discovery Technology and Platforms is a newly established function within this organization. Its mission is to accelerate molecule discovery by building highly optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and intentionally investing in novel technologies and capabilities.

Frontier AIis a purpose-built team that fuses scientific agentic AI, lab automation, and unified data platforms to autonomously design, run, and refine experiments-accelerating molecule discovery.

Position Summary

We are rebuilding the Design-Make-Test-Analyze (DMTA) cycle, infusing scientific automation with foundation models, multi-agent systems, and robotics to make scientific discovery intelligent, autonomous, and fast.

We're seeking a scientist-engineer hybrid to design the learning layer of our scientific agent platform. You will design the environments, rewards, and domain-specific models that enable agents to improve based on experimental feedback. You'll translate wet-lab and computational endpoints into a trainable signal to build models that plan and act against them.

Responsibilities:

Research & Innovation

  • Partner with scientists to build autonomous agents that undertake molecule discovery tasks

  • Design and build reinforcement learning (RL) environments that wrap real discovery tasks with appropriate state, action, and termination semantics.

  • Curate and engineer reward functions from noisy scientific signal.

  • Post-train domain models (SFT, DPO/GRPO/PPO, reward modeling, distillation) on chemistry and biology tasks

  • Integrate learned policies with domain tools (RDKit, molecular graph ML, ELN/LIMS APIs, instrument drivers) so trained models execute real DMTA tasks

  • Build the eval infrastructure: task suites, scoring harnesses, regression tracking, and experiment tracking (e.g., MLflow)

External Engagement

  • Represent Frontier AI in the broader AI@Lilly and external AI research community: publish, give talks, review papers, and scout emerging trends.

  • Evaluate external vendors, open-source projects, and academic collaborations for strategic fit.

What Success Looks Like

  • Trained models that measurably outperform prompted frontier baseline models on internal discovery tasks

  • Reward and evaluation infrastructure that other teams adopt as the default way to measure agent performance

  • Measurable reduction in DMTA turnaround through autonomous planning and execution

  • Seamless transition from prototype to production-deployed AI systems

Basic Qualifications:

  • PhD (or MS + 3 yrs / BS + 5 yrs equivalent experience) in Machine Learning, Bioinformatics, Cheminformatics, Computer Science, or related STEM field with demonstrated wet-lab collaboration or hands-on experience.

  • Approximately 1-2 years of demonstrated experience in applying AI/ML in scientific disciplines such as biology, chemistry, neuroscience, or a related field (industry postdoc counts)

  • Hands-on experience training or post-training AI models

Additional Preferences:

  • Proficiency in Python and deep experience with ML/Deep Learning frameworks (e.g., PyTorch, Tensorflow, JAX, HuggingFace).

  • Experience with RL and post-training methods (PPO, GRPO, DPO, reward modeling, RLHF/RLAIF) and libraries such as TRL, verl, or equivalent in-house stacks

  • Familiarity with molecular representation learning, generative chemistry, or protein/nucleic acid models

  • Hands-on experience building agentic AI systems (e.g., OpenAI/ Anthropic Agent SDK, Langchain, Smol agents)

  • Experience designing and shipping end-to-end systems in cloud environments (backend APIs, lightweight frontends, and agentic platforms)- GitHub portfolio a plus

  • Working knowledge of cloud-native (AWS/Azure) pipeline architectures, including Nextflow, Argo on Kubernetes

  • Demonstrable research experience, evidenced by contributions to projects, and ideally through publications in relevant ML/NLP venues (e.g.,NeurIPS, ICML, ICLR, ACL, EMNLP).

  • Experience mentoring and guiding junior researchers or engineers.

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 (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women's Initiative for Leading at Lilly (WILL).


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

$151,500 - $222,200

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

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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