Role Overview We are seeking a highly motivated AI Researcher with a Ph.D. in Mathematics or Physics to join our research team. You will contribute to the development of cutting-edge AI models applied to biological data, collaborating with scientists and engineers to drive discovery and innovation. Develop, analyze, and optimize advanced machine learning models, including deep learning and probabilistic models, tailored to biomedical applications. Conduct theoretical and applied research bridging mathematics/physics with biological systems and data. Collaborate with domain experts to frame complex biological challenges into solvable AI problems. Design and implement experiments to validate model performance on real-world biological datasets (e.g., genomics, proteomics, medical imaging). Publish findings in top-tier journals and conferences, and contribute to patents and IP development. Stay current with the latest research in AI, applied mathematics, and computational biology. Qualifications Ph.D. in Mathematics, Physics, or a closely related field. Strong background in one or more of the following: statistical mechanics, optimization, information theory, Bayesian inference, or numerical modeling. Solid programming skills in Python and experience with machine learning libraries (e.g., PyTorch, TensorFlow, JAX). Ability to work with large-scale, high-dimensional datasets. Excellent problem-solving and mathematical modeling skills. Strong communication skills and the ability to work in an interdisciplinary team. Preferred Qualifications Experience with AI applications in biology, chemistry, or healthcare. Familiarity with bioinformatics tools and biological data formats (e.g., FASTA, VCF). Previous publications or projects in applied AI research.

About ThinkBio.Ai ThinkBio.Ai is revolutionizing the biopharmaceutical and healthcare fields with AI-powered resources. Our five specialized teams clinical, science, AI, software, and managed services work together to develop AI-based solutions that are deployed horizontally (data platforms and workflow tools) and vertically (clinical focus areas such as oncology, autoimmune diseases, and cardiology). Our mission is to help our clients find answers to their toughest questions and to accelerate the application of scientific breakthroughs in the clinic. Position Summary: We are seeking a highly motivated individual with expertise in computational chemistry to join our team as a Postdoctoral Fellow or Scientist, depending on experience level. The position will involve applying advanced computational methods to design, optimize, and analyze small molecules and their interactions with biological targets, contributing to drug discovery and disease modeling efforts. The successful candidate will have a PhD in computational chemistry, cheminformatics, physical chemistry, or a related field, with a deep understanding of molecular modeling, simulations, and structure-activity relationships. Fresh PhD graduates will be hired as Postdoctoral Fellows for a two-year term, while candidates with at least two years of postdoctoral fellowship or industry experience will be considered for a Scientist position. : Apply deep domain knowledge in computational chemistry to support drug discovery projects, including virtual screening, lead optimization, and ADME/Tox predictions. Utilize molecular modeling, molecular dynamics simulations, quantum mechanics, and docking techniques to understand ligand-protein interactions and predict binding affinities. Integrate chemical data with multi-omics data (genomics, transcriptomics, proteomics, and metabolomics) to identify novel therapeutic opportunities and understand disease mechanisms. Work with a team of computational biologists and software experts to develop and apply AI/ML approaches for chemical property prediction and drug design. Stay up to date with the latest advancements in computational chemistry, cheminformatics, and AI-driven drug discovery to incorporate cutting-edge research into project efforts. Collaboration & Project Management: Work closely with cross-functional teams, including medicinal chemists, biologists, computational scientists, and software engineers to enhance translational research efforts. Work with the Scientific Manager to help in project planning, execution, and reporting, ensuring alignment with research objectives. Communicate findings effectively through reports, presentations, and discussions with internal teams and external collaborators. Publish research findings in high-impact, peer-reviewed journals. Present work at scientific conferences, symposia, and internal research meetings. Contribute to grant applications and funding proposals where relevant. Qualifications & Experience: PhD in computational chemistry, cheminformatics, physical chemistry, or a closely related field. Strong expertise in molecular modeling, molecular dynamics simulations, quantum mechanics, and virtual screening techniques. Solid understanding of drug discovery principles, medicinal chemistry concepts, and structure-activity relationships. Proficiency with relevant computational chemistry software (e.g., Schr dinger, OpenEye, GROMACS, Amber) and programming languages (e.g., Python, R). Excellent verbal and written communication skills, with the ability to convey complex chemical and computational concepts clearly. Preferred: Experience with large-scale chemical data analysis and cheminformatics tools. Experience applying machine learning or artificial intelligence to chemical problems. Previous experience working in a multidisciplinary research environment, especially in a biopharmaceutical setting. Other Considerations: Fresh PhD graduates will be hired as Postdoctoral Fellows for a two-year term with an opportunity for promotion to Scientist based on performance. Candidates with at least two years of postdoctoral experience in computational chemistry in either academia or industry will be hired as Scientists with opportunities for career advancement. Why Join Us? Work at the cutting edge of computational chemistry and AI-driven drug discovery. Contribute to groundbreaking disease modeling and omics integration efforts. Collaborate with leading experts in multiple disease domains. Competitive salary, benefits, and career development opportunities. Application Instructions: Interested candidates should submit a cover letter and CV to careers@thinkbioai.com .

About ThinkBio.Ai ThinkBio.Ai is revolutionizing the biopharmaceutical and healthcare fields with AI-powered resources. Our five specialized teams clinical, science, AI, software, and managed services work together to develop AI-based solutions that are deployed horizontally (data platforms and workflow tools) and vertically (clinical focus areas such as oncology, autoimmune diseases, and cardiology). Our mission is to help our clients find answers to their toughest questions and to accelerate the application of scientific breakthroughs in the clinic. Position Summary: We are seeking a highly motivated individual with expertise in structural biology to join our team as a Postdoctoral Fellow or Scientist, depending on experience level. The position will involve applying structural biology techniques to understand protein-protein interactions, drug-target binding, and disease mechanisms, integrating these insights into computational models. The successful candidate will have a PhD in structural biology, biophysics, biochemistry, or a related field, with a deep understanding of macromolecular structure and function. Fresh PhD graduates will be hired as Postdoctoral Fellows for a two-year term, while candidates with at least two years of postdoctoral fellowship or industry experience will be considered for a Scientist position. : Apply deep domain knowledge in structural biology to characterize macromolecular complexes and understand their roles in disease pathways. Integrate structural insights with multi-omics data (genomics, transcriptomics, proteomics, and metabolomics) to understand molecular mechanisms of disease. Utilize and develop computational tools for structural modeling, molecular dynamics simulations, and ligand docking to complement experimental data. Stay up to date with the latest advancements in structural biology, biophysics, and computational methods to incorporate cutting-edge research into disease modeling efforts. Collaboration & Project Management: Work closely with cross-functional teams, including disease domain experts, computational scientists, and clinicians to enhance translational research efforts. Work with the Scientific Manager to help in project planning, execution, and reporting, ensuring alignment with research objectives. Communicate findings effectively through reports, presentations, and discussions with internal teams and external collaborators. Publish research findings in high-impact, peer-reviewed journals. Present work at scientific conferences, symposia, and internal research meetings. Contribute to grant applications and funding proposals where relevant. Qualifications & Experience: PhD in structural biology, biophysics, biochemistry, or a closely related field. Strong expertise in at least one major structural biology technique (e.g., X-ray crystallography, cryo-electron microscopy (cryo-EM), NMR spectroscopy). Solid understanding of protein structure-function relationships, macromolecular interactions, and their relevance to disease biology. Experience in experimental design, data collection, data processing, and structure determination. Excellent verbal and written communication skills, with the ability to convey complex structural biology concepts clearly. Preferred: Experience with computational structural biology tools (e.g., Rosetta, AlphaFold, molecular dynamics software). Previous experience working in a multidisciplinary research environment. Familiarity with AI/ML approaches in structural biology or drug discovery. Other Considerations: Fresh PhD graduates will be hired as Postdoctoral Fellows for a two-year term with an opportunity for promotion to Scientist based on performance. Candidates with at least two years of postdoctoral experience in structural biology in either academia or industry will be hired as Scientists with opportunities for career advancement. Why Join Us? Work at the cutting edge of structural biology and disease research. Contribute to groundbreaking disease modeling and molecular insights. Collaborate with leading experts in multiple disease domains. Competitive salary, benefits, and career development opportunities. Application Instructions: Interested candidates should submit a cover letter and CV to careers@thinkbioai.com .

As a Data Curator, you will be responsible for organizing, managing, and maintaining a diverse range of biological and clinical datasets. You will work closely with researchers, bioinformaticians, and software engineers to ensure data quality, accessibility, and compliance with industry standards. Your role will involve data collection, integration, annotation, and documentation to support research and clinical projects. Data Collection & Integration: Gather and integrate data from various sources, including genomic studies, clinical trials, EHRs, and public databases. Data Cleaning & Quality Control: Perform quality checks to ensure data accuracy, consistency, and completeness. Identify and correct errors and inconsistencies Data Annotation: Tag and categorize data to facilitate easy retrieval and analysis. Prepare data for specific research or clinical applications. Compliance: Ensure data handling practices comply with regulatory standards and ethical guidelines, including patient confidentiality and data security. Collaboration: Work with researchers, clinicians, software engineers and other stakeholders to understand their data needs and provide curated data for analysis and decision-making. Standards & Guidelines: Assist in the development and adherence to data standards and best practices. Ensure alignment with treatment guidelines and clinical standards. Communication: Good communication skills and ability to write and submit project proposals/grants to gain access to data Qualifications Educational Background: Bachelor s or Master s degree in Biology, Biotechnology, Bioinformatics, Health Informatics, Clinical Research, or related fields. Experience: Proven experience in data management, curation, or bioinformatics, with a background in biotech or clinical research preferred. Technical Skills: Experience with database management systems (e.g., SQL), data visualization tools, and programming languages (e.g., Python, R) a plus.

About ThinkBio.Ai ThinkBio.Ai is revolutionizing BioPharma and Clinical Healthcare with AI-powered solutions. Our five specialized teams clinical, science, AI, software, and managed services develop horizontal solutions like data platforms and workflow tools and vertical solutions focused on areas like oncology, autoimmune diseases, and cardiology. Our mission is to help our clients find answers to their toughest questions and accelerate breakthroughs from research to the clinic. Position Summary Excellent opportunities are available to engage in cutting edge projects for building digital/AI solutions for biomedical research cycle-based discovery and development of innovations. We are looking for enthusiastic and energetic life science scientists (PhD level) with a passion for learning and impacting human lives by facilitating scientific discoveries through digital technology. Job Description Systematically classify various domains and subdomains of biomedical discovery research process. Identify opportunities for creating digital solutions to assist biomedical research scientists. Reimagine biomedical research process and visualize how innovative digital/AI platform can transform innovations in biological sciences. Interface with software and AI teams to facilitate their understanding of various research processes underlying biomedical sciences, help realize the gaps that can be solved with digital platforms Work with the digital tech team to facilitate the creation of digital solutions for biological sciences Work with the leadership to identify key areas of biomedical commercial opportunities. Conduct routine market analysis, spot emerging business opportunities, inform ThinkBio leadership Manage associates. Participate and present results at cross-functional team meetings. Contribute to building a positive, team-oriented work culture. Essential qualifications Curious, driven, passionate, aspires to use science and digital solutions to make human lives better. PhD in any branch of biological sciences with experience in the broad areas related to cell, genome, biochemistry and therapeutic discovery. Significant understanding of the broader biomedical research and various processes related to discovery and innovations of new aspects of biology and/or drugs (e.g., cell biology, mechanism of action discovery, phenotypic assays, biochemical assays, immunology, genomics, protein engineering, drug screening, mammalian cell and genome engineering, cell signalling, drug discovery screening, or related fields). Familiarity with a wide range of experimental approaches. Enjoys conceiving ideas, and driving experimental approaches to convert ideas as measurable results. Knowledge seeker with a passion for learning about new technologies. Demonstrated ability to present in scientific conferences and internal meetings. Motivated, team oriented, thriving in matrix format work environment with diverse technical expertise. Attention to detail and demonstrated ability in multi-tasking, in a fast-paced environment. Ability to adapt to changing priorities, coupled with demonstrated eagerness to learn new technologies. Curiosity to dive below the obvious and proactively identify critical issues or opportunities. Desirable additional experience Experience in the following area is highly desirable, but not essential. Experience working with digital platforms for biomedical research

About ThinkBio.Ai ThinkBio.Ai is revolutionizing the biopharmaceutical and healthcare fields with AI-powered resources. Our five specialized teams clinical, science, AI, software, and managed services work together to develop AI-based solutions that are deployed horizontally (data platforms and workflow tools) and vertically (clinical focus areas such as oncology, autoimmune diseases, and cardiology). Our mission is to help our clients find answers to their toughest questions and to accelerate the application of scientific breakthroughs in the clinic. Position Summary: We are seeking a highly motivated individual with expertise in computational biology to join our team as a Postdoctoral Fellow or Scientist, depending on experience level. The position will involve developing and applying computational methods to integrate multi-omics data for disease modeling and understanding biological mechanisms. The successful candidate will have a PhD in computational biology, bioinformatics, systems biology, or a related field, with a deep understanding of analyzing large-scale biological datasets. Fresh PhD graduates will be hired as Postdoctoral Fellows for a two-year term, while candidates with at least two years of postdoctoral fellowship or industry experience will be considered for a Scientist position. : Apply deep domain knowledge in computational biology to develop and refine disease models using diverse biological data. Integrate multi-omics data (genomics, transcriptomics, proteomics, and metabolomics) to identify key biological insights and mechanisms. Develop and implement computational pipelines and algorithms for the analysis of complex biological data from public and proprietary sources. Stay up to date with the latest advancements in computational biology, bioinformatics, and systems biology to incorporate cutting-edge research into disease modeling efforts. Collaboration & Project Management: Work closely with cross-functional teams, including disease domain experts, experimental scientists, and software engineers to enhance translational research efforts. Work with the Scientific Manager to help in project planning, execution, and reporting, ensuring alignment with research objectives. Communicate findings effectively through reports, presentations, and discussions with internal teams and external collaborators. Publish research findings in high-impact, peer-reviewed journals. Present work at scientific conferences, symposia, and internal research meetings. Contribute to grant applications and funding proposals where relevant. Qualifications & Experience: PhD in computational biology, bioinformatics, systems biology, or a closely related field. Strong expertise in analyzing and interpreting large-scale biological datasets, including genomics, transcriptomics, proteomics, or metabolomics. Solid understanding of disease biology, with the ability to contextualize computational findings within broader disease mechanisms. Proficiency in programming languages commonly used in computational biology (e.g., Python, R) and experience with relevant software tools and databases. Excellent verbal and written communication skills, with the ability to convey complex computational concepts clearly. Preferred: Experience with machine learning or artificial intelligence techniques applied to biological data. Previous experience working in a multidisciplinary research environment. Familiarity with cloud computing environments and high-performance computing. Other Considerations: Fresh PhD graduates will be hired as Postdoctoral Fellows for a two-year term with an opportunity for promotion to Scientist based on performance. Candidates with at least two years of postdoctoral experience in computational biology/bioinformatics in either academia or industry will be hired as Scientists with opportunities for career advancement. Why Join Us? Work at the cutting edge of computational biology and disease modeling. Contribute to groundbreaking disease modeling and omics integration efforts. Collaborate with leading experts in multiple disease domains. Competitive salary, benefits, and career development opportunities. Application Instructions: Interested candidates should submit a cover letter and CV to careers@thinkbioai.com .

About ThinkBio.Ai At ThinkBio.AI , we are more than just a software company - we are partners in transformation. Our mission is to revolutionize the Health Sciences, Biotech, and Pharma industries through the power of AI. What sets us apart is our unique blend of deep industry expertise and cutting-edge AI capabilities. We deliver seamless integration with existing systems, offer tailored solutions for global markets, and implement automated processes that optimize workflows. Job Overview We are seeking a dynamic and experienced Manager Pre-Sales, Solutions definition and Proposals, to join our team. The ideal candidate will have a proven track record in assisting the sales team in analyzing customer needs, developing, and presenting technical solutions, and driving the successful conversion of sales opportunities. You will play a crucial role in expanding our market presence, building strong relationships with clients, and driving revenue growth. Key Responsibilities Develop and implement a presales strategy and processes that align with sales and marketing objectives Support the sales team in qualifying leads and documenting customer requirements Propose solutions based on customer needs and business goals Create proposals and responses to RFPs Provide product demonstrations, presentations, proposals, and proofs of concept to potential and existing customers Foster strong relationships with clients and internal stakeholders. Qualifications Education : Bachelor s in Information Technology or related field and MBA in Marketing, Sales, or related field Experience : 3-5 years relevant experience in pre-sales/sales role including familiarity with the technical features and market demands of software products. Significant exposure to the US market is a necessity. Industry Knowledge : Strong understanding of the healthcare or biotech industry, including key players and market trends along with familiarity with AI domains. Communication: Excellent verbal and written communication skills, with the ability to present complex products and services clearly to customers Client Management: Strong interpersonal skills for building and maintaining client relationships Tech Proficiency: Familiar with CRM systems and sales automation tools

At ThinkBio.Ai we are adding Intelligence to Digital Biology. We leverage our deep expertise in Biotech, Pharma, Health Sciences, and AI, along with our experience in software development to provide platforms, toolkits, and solutions. Excellent opportunities are available to engage in cutting edge research using engineered biology-based approaches and frontier emerging areas of synthetic biology, to create transformative contributions in human drug discovery and development. We are looking for an enthusiastic and energetic Data and Computational scientist with a passion for learning and impacting human lives through scientific discoveries. Key Responsibilities Help refine, develop, and build the data analytics and computational strategy for ThinkBio.Ai Develop and apply computational/statistical methods to analyze various inhouse and externally sourced data including those related to biological experiments or human population parameters such as disease burden, genetic variation, cause-effect association etc. Analyze complex multi-omics data sets across various parameters and connect insights and observations to actionable hypotheses. Synthesize provided data into actionable insights by supporting any needed computational, statistical, machine learning or modeling capabilities needed to enable strategic decision making and advance our clinical and research programs. Develop and apply tailored data analytical and computational methods/techniques to advance both our clinical and research programs. Develop novel computational platforms and pipelines to identify novel therapeutic targets, and to discover biomarkers for drug response, patient stratification Ability to integrate validated data analysis tools and pipelines from public resources to create robust data analysis and interpretation pipelines for visualization and integrative analysis, and interactive dashboards to create insightful visualization and interpretation of data. Work closely with other team members and partners to identify most critical data centered challenges and address them using cutting-edge computational, statistical and machine learning applications. Required Qualifications and Skills Ph.D. or Masters in Computer science, Data science, Statistics, Bioinformatics or related fields. 10+ years experience and technical expertise in applied bioinformatics, computational biology, data science or biostatistics. Robust working knowledge and application of data analysis and modeling, data wrangling and data visualization. Firm grasp of modern statistical methods and machine learning techniques, and their applications to large-scale, high throughput dataset analysis. Proficiency with R/ Bioconductor, Python or equivalents, and relational databases (SQL, NoSQL). First-hand experience in multi-parametric data mining, analysis and visualization in any biomedical application. Exposure to multi-parametric data mining experience for disease stratification/endotyping, target identification and biomarker analysis. Experience and understanding of how bioinformatics and data science can best be applied to speed up drug discovery. Basic understanding of biological concepts and a familiarity with drug development process Knowledge of bioinformatic tools and databases to analyze genomics and proteomics data Ability to manage projects with minimal supervision, using creative and analytical thinking. Ability to drive highly collaborative work across the organization and outside the company Excellent oral and written communication. Desirable Additional Experience Experience in one or more of the following areas is highly desirable, but not essential. Deeper knowledge/training/experience in biomedical field. A minimum of 1-year research (academia or industry) experience. Demonstrated experience in deep learning and generative AI model based approaches such as bioinformatics foundation models (BFMs). Experience in genomics, transcriptomics, Next Generation Sequencing (NGS) analysis, single cell RNAseq, flow cytometry or IHC based data processing. Experience working with one or more of the following disciplines: synthetic biology, comparative genomics, population genetics, probabilistic modeling, population genetics, and quantitative modeling of biological systems. Experience with one or more of the following: P Snakemake, Nextflow, airflow, CWL, relational databases (SQL), GraphQL, distributed computing (AWS/Google Cloud), Docker, software version control (git). Managing a data analytics and computational operating model that encompasses processes and technologies for executing scalable data management solutions for various data types.