Senior Scientist / Principal Scientist, AI & Computational Drug Discovery

Confidential Biotechnology / AI Company

Florida Hybrid | Major Florida Metropolitan Area Preferred
Base Compensation: $130,000 to $195,000, depending on experience and appointment level

ABOUT THE OPPORTUNITY

A Florida-based biotechnology and artificial intelligence company is seeking an exceptional Senior Scientist or Principal Scientist in AI and Computational Drug Discovery.

The company is advancing multiple therapeutic discovery and technology programs at the intersection of artificial intelligence, molecular simulation, structural biology, computational chemistry, and translational drug development. Its research environment includes externally funded programs and work that may involve U.S. Government-supported research.

This is not a narrowly scoped computational analyst position. We are seeking a scientist who can take a difficult biological or drug-discovery problem from scientific question through computational strategy, implementation, rigorous analysis, biological interpretation, and experimentally actionable conclusions.

The successful candidate should understand the science behind the computational methods, not simply how to operate existing software. The role requires strong scientific judgment, technical independence, programming ability, high productivity, rapid learning, and the capacity to advance multiple complex research programs simultaneously.

WHAT YOU WILL DO

The successful candidate will:

- Independently design and execute computational drug-discovery and molecular-design strategies.

- Apply AI and machine learning to molecular property prediction, predictive modeling, virtual screening, compound prioritization, and molecular design.

- Perform molecular docking, structure-based drug design, molecular dynamics simulations, and protein-ligand analyses.

- Design and execute enhanced-sampling or related advanced molecular simulation approaches when conventional MD is insufficient.

- Analyze protein structure, conformational dynamics, mutations, structure-function relationships, protein-protein interactions, and protein-ligand interactions.

- Write, modify, and troubleshoot scientific code and computational workflows rather than relying exclusively on predefined software pipelines.

- Integrate computational findings with molecular biology, biochemistry, pharmacology, disease biology, ADMET, and experimentally testable hypotheses.

- Work effectively with GPU-based computational environments, scientific servers, Linux-based systems, and large scientific datasets.

- Critically evaluate model performance, simulation quality, sampling adequacy, convergence, uncertainty, assumptions, and methodological limitations.

- Translate computational results into biologically meaningful conclusions and actionable experimental or drug-development decisions.

- Independently manage several technically complex research programs while maintaining scientific rigor, documentation, accountability, and execution velocity.

CORE TECHNICAL QUALIFICATIONS

Strong candidates should demonstrate substantial capability across the core disciplines of computational drug discovery, molecular modeling, and AI-enabled molecular science.

Particularly relevant expertise includes:

- Molecular dynamics simulation and molecular docking
- Structure-based drug design
- Enhanced-sampling molecular dynamics
- Protein structural biology, conformational dynamics, and molecular interactions
- AI and machine learning for molecular science
- Scientific programming, particularly Python or comparable languages
- Computational chemistry, biophysics, cheminformatics, or molecular modeling
- Biological and pharmacological interpretation of computational results

Candidates should have direct hands-on experience performing scientific analyses themselves and should be able to explain the rationale, assumptions, limitations, validation requirements, and biological implications of their work.

The ability to operate scientific software packages is not by itself sufficient. We are looking for scientists who understand why a method is being used, when it is appropriate, how to troubleshoot it, how to determine whether the result is credible, and what the result means scientifically.

ADVANCED MOLECULAR SIMULATION AND AI

Experience with enhanced-sampling molecular dynamics is particularly valuable. Relevant experience may include metadynamics, umbrella sampling, replica-exchange methods, accelerated MD, adaptive or biased sampling, free-energy calculations, conformational landscape analysis, or related advanced simulation approaches.

Candidates with this experience should understand not simply how to initiate calculations, but when advanced sampling is appropriate, how methodological choices should be made, and how sampling quality and convergence should be evaluated.

Relevant AI and machine-learning experience may include molecular property prediction, deep learning or graph-based molecular modeling, generative molecular design, virtual screening, compound prioritization, structure-informed machine learning, sequence-structure-function modeling, or integration of biological, chemical, structural, and experimental datasets.

We value genuine understanding of model construction, validation, interpretation, and scientific application more than familiarity with a long list of packages or frameworks.

BIOLOGICAL AND DRUG-DEVELOPMENT INTERPRETATION

The successful candidate should be able to move beyond computational output and ask:

What biological mechanism does this result support?

Is the observation biologically plausible?

What alternative explanations should be considered?

What experiment should be performed next?

What would validate or falsify the proposed mechanism?

Does this result materially change a drug-discovery decision?

A strong foundation in molecular biology, biochemistry, pharmacology, disease biology, ADMET, or related areas is therefore highly desirable.

ADDITIONAL EXPERTISE OF INTEREST

Additional experience in one or more of the following areas would be advantageous:

- Generative AI for molecular design
- Advanced ADMET modeling
- Free-energy methods
- Cryptic or allosteric binding-site analysis
- Mutation and variant modeling
- GPU/HPC scientific computing
- Scientific workflow automation and computational software development
- RNA or DNA structural modeling
- RNA-protein or DNA-protein interactions
- Aptamers or nucleic-acid therapeutics
- Medicinal chemistry or translational disease biology

Exceptional scientists will naturally have particular areas of depth. We are seeking deep technical capability combined with intellectual range and rapid learning rather than expecting every candidate to have worked previously in every area relevant to the organization.

SCIENTIFIC OWNERSHIP

This position requires considerably more than execution of assigned computational tasks.

The successful candidate should be capable of receiving an important scientific objective and independently determining the underlying biological question, computational strategy, required data and controls, implementation, validation criteria, and how technical problems should be resolved.

The strongest candidate will be someone who can receive a complex scientific objective, independently determine an appropriate strategy, execute and troubleshoot the work, critically interpret the results, and return to scientific leadership with defensible conclusions and recommendations for next steps.

We are specifically seeking someone who increases the technical capacity of the broader research organization through independent scientific ownership rather than requiring continual technical supervision.

EDUCATION AND EXPERIENCE

A PhD in computational chemistry, computational biology, biophysics, cheminformatics, medicinal chemistry, structural biology, machine learning, bioinformatics, molecular modeling, or a closely related discipline is preferred.

Exceptional candidates with an MS or other training combined with substantial demonstrated scientific and computational expertise will also be considered.

Demonstrated capability matters more than degree title alone. This is, however, a senior scientific position requiring substantial independent research capability and is not intended as an entry-level computational analyst role.

Appointment at the Senior Scientist or Principal Scientist level will depend on scientific accomplishments, technical depth, breadth of expertise, independence, experience, and demonstrated ability to advance complex research programs.

WHAT WE VALUE

We are particularly interested in scientists who demonstrate intellectual independence, scientific rigor, high productivity, strong analytical reasoning, technical depth, rapid learning, ownership of difficult problems, strong scientific communication, and the ability to manage multiple research programs.

The successful candidate should be comfortable operating across disciplinary boundaries and in a fast-moving entrepreneurial research environment where priorities may evolve as new results, collaborations, funding opportunities, or biological insights emerge.

The objective is to recruit a scientist who materially increases the scientific and technical capacity of the organization.

LOCATION AND WORK MODEL

This is a Florida-based hybrid position.

The position may initially involve substantial remote work. The successful candidate must establish and maintain primary residence in Florida and an appropriate Florida payroll address in accordance with applicable program and funding requirements.

Candidates may reside anywhere in Florida. Residence in or near a major Florida metropolitan area is preferred because the position will involve periodic in-person scientific collaboration and team activities.

The company maintains a flexible work environment rather than a rigid weekly office schedule. However, this is not intended to become a permanently isolated 100 percent remote role. Meaningful in-person scientific interaction is expected so that the successful candidate becomes fully integrated into the research organization.

COMPENSATION

Expected base compensation is $130,000 to $195,000 annually, depending upon experience, scientific accomplishments, technical depth, breadth of expertise, research independence, and appointment level.

U.S. WORK AUTHORIZATION AND GOVERNMENT PROGRAMS

Applicants must be authorized to work in the United States without current or future employer sponsorship.

This position may support U.S. Government or Department of Defense-funded research programs. The successful candidate must therefore be eligible to satisfy applicable contractual, security, export-control, personnel, or program-specific access requirements.

Certain assignments may carry additional eligibility requirements, including U.S. citizenship where specifically required by the applicable contract, regulation, security requirement, or program.

CONFIDENTIAL SEARCH

The company's identity is being withheld during the initial application stage to maintain a structured and confidential recruitment process.

Candidates selected to advance will receive the company identity and additional information about its scientific programs before the first substantive interview so they can independently evaluate both the organization and the opportunity before proceeding.

APPLICATION AND INTERVIEW PROCESS

Applicants should submit a CV or résumé through this LinkedIn posting.

Please apply through the formal application process rather than attempting to identify or directly contact company leadership regarding the position. Direct LinkedIn messages, unsolicited emails, or other outreach will not substitute for an application and will not provide preferential consideration.

Candidates are encouraged to identify one or two projects for which they personally had substantial technical and intellectual responsibility, particularly projects involving molecular simulation, computational drug discovery, AI/ML, structural biology, or scientific software development.

Applicants should clearly distinguish work they personally designed and executed from work performed primarily by collaborators or other members of a research group.

Selected candidates should expect substantive scientific discussion during the interview process. We want to understand how candidates reason through difficult scientific problems, choose methods, evaluate alternatives, troubleshoot computational work, assess validity and convergence, interpret biological significance, and determine what should happen next.