2 Uniprot Jobs

Scientific Lead Medicine moves too slow. At Velsera, we are changing that. Velsera was formed in 2023 through the shared vision of Seven Bridges and Pierian, with a mission to accelerate the discovery, development, and delivery of life-changing insights. Velsera provides software and professional services for: AI-powered multimodal data harmonization and analytics for drug discovery and development IVD development, validation, and regulatory approval Clinical NGS interpretation, reporting, and adoption With our headquarters in Boston, MA, we are growing and expanding our teams located in different countries! Designation: Scientific Lead Location: Pune, India (Hybrid) As a Scientific Lead, you will report to the Manager KB and your tasks will consist of application on strong molecular biology and cancer biology background to curate, interpret and represent data from variety of sources into logical rules that form the core of our clinical genomics knowledgebase. What will you do? Technical/Scientific Demonstrate clear understanding of therapies, drug mechanism of action, oncology disease biology, biomarker/mutation, the structure and the construction of KB rules, how it is applied to patient cases. Ability to analyze association of clinical recommendations of predictive, diagnostic, and prognostic recommendation for Oncology gene panels for NGS test. Ability to understand disease ontologies (example, WHO, SNOMED etc.) to construct custom disease ontology based on disease pathology and molecular cellular subtypes. Demonstrate understanding of somatic variant classification & classification hierarchy like AMP/ASCO/CAP classification, Germline variant classification like ACMG classification. Act as the accountable owner for curation of clinical content sources which includes clinical practice guidelines, approved drug labels (FDA, EMA), clinical trials and PubMed and take responsibility for overall QC/QA of the data curated by the team, ensuring delivery of high-quality data. - Contribute as reviewer of the curated content to review. - Review existing curation strategies and clinically significant data that is curated. - Understand usage of curated data is in the reporting platform and the impact on the patient care. SOPs &/or Work Instruction (WI) - Create/design workflow for new clinical content curation strategy or extrapolate existing curation strategies to a similar new biomarker/mutation scenario classifying variants for clinical NGS reporting. - Create/design SOPs &/or Work Instruction (WI) generation for the clinical oncology data curation process. - Identify potential risks of process, project or design, and report deviation from SOP or WI - Identify gaps or misalignment between written WI and workflow implementation and propose solutions. Demonstrate new ideas and ability to present and defend ideas in team or change control board meetings. Demonstrate problem solving mindset - provide clear solutions or take decisions to resolve blockers in day-to-day tasks and be able to support/justify them in scientifically acceptable way or by providing necessary evidence. Ability to ensure path for clinically conflicting data and observations within team Perform impact analysis for the deviation and propose a solution that is practical and accurate Initiate and drive discussions to ensure high quality KB adhering to the regulatory and customer requirements. Understand of content curation workflow thoroughly and come up with possible optimization and efficiency using upcoming technologies. Identify technology tooling requirements/enhancements to improve clinical content curation workflow. Act as a strong partner of the engineering team for software automation of scientific decision algorithms - ability to contribute towards process design and software design reviews. Provide mentorship to juniors and reviewers on clinical content strategies helping them to scale up. Demonstrate thought leadership: You should be seen as a reference and go-to person for niche expertise. Open to self-training and exploring new technologies. Communications Should be able to initiate discussions and communicate issues within team or across teams with clear background understanding to achieve outcome or conclusions. Initiate or engage in clear communication (slack, email, and verbal) regarding any blocker / issues with members of (other) teams, follow-up and conclude. Ability to develop documentation, power point presentations, flowcharts, diagrams etc. to communicate technical solutions. Operational Should have a strong sense of commitment, ownership & urgency and stay aligned with the SLAs. Establish strong tracking, quality control and communication (internal and external) methods of timely delivery. Decision making: Provide guidance in decision making to the team in case of blocker issues. Coach and train the team to take independent scientific decisions, tradeoffs and strong prioritization. Identify needs, gather supporting evidence to devise or come up with proposals for newer processes/workflows. Identify ways to increase team velocity and efficiency. For example, identify areas where automation would help and accordingly provide ‘requirements’ for tool development. Plan and execute POC for new projects or sub tasks. Create and Own POC plans; Contribute towards planning, projects, and delivery schedules. Execute plans with ownership and commitment; track progress with clear communication. Author/update SOPs, strategy documents, marketing material and compliance documentation. Enable teams to follow, execute on the SOPs. Content documentation – document and review content related approach in scientific and methodical manner Manage different types of complexities in the workflow. Training - Design, document and execute existing or revised training workflows and conduct training as per SOP/WI. - Identify the training needs within the team or specific team member to improve efficiency and quality of the data delivered. Take a lead in solving problems or small projects, be proactive and own results. Should provide regular peer feedback to the team/functional leads. Demonstrate strong adherence to Velsera core values. What do you bring to the table? Ph.D. in genetics, genomics, molecular biology, or an equivalent with 4+ years of postdoc or work experience OR - Master’s degree in molecular biology, genetics, biotechnology, or biochemistry with 8+ years of work experience Genetic and molecular understanding of human disease. Good understanding of genomic databases and their annotations (For example: ClinVAR, Uniprot, GenBank, RefSeq, dbSNP, gnomAD, Cosmic, OMIM etc.). Basic understanding of cancer biology and signaling pathways. An understanding of bioinformatics analysis to identify variants within genomic data sets is desirable. Proficiency in communicating and understanding of genetic variant details. An enthusiastic "can-do" mentality with leadership skills, a dedicated team-worker, having good verbal and written communication skills. Previous experience as an experimental scientist in applied science or hands-on experience in oncogenomic diagnostic laboratories is a big plus. Experience with open-source bioinformatics tools and publicly available variant databases is a plus. Personal initiative and ability to work effectively as part of a team. Excellent communication skills. Our Core Values People first. We create collaborative and supportive environments by operating with respect and flexibility to promote mental, emotional and physical health. We practice empathy by treating others the way they want to be treated and assuming positive intent. We are proud of our inclusive diverse team and humble ourselves to learn about and build our connection with each other. Patient focused. We act with swift determination without sacrificing our expectations of quality . We are driven by providing exceptional solutions for our customers to positively impact patient lives. Considering what is at stake, we challenge ourselves to develop the best solution, not just the easy one. Integrity. We hold ourselves accountable and strive for transparent communication to build trust amongst ourselves and our customers. We take ownership of our results as we know what we do matters and collectively we will change the healthcare industry. We are thoughtful and intentional with every customer interaction understanding the overall impact on human health. Curious. We ask questions and actively listen in order to learn and continuously improve . We embrace change and the opportunities it presents to make each other better. We strive to be on the cutting edge of science and technology innovation by encouraging creativity. Impactful. We take our social responsibility with the seriousness it deserves and hold ourselves to a high standard. We improve our sustainability by encouraging discussion and taking action as it relates to our natural, social and economic resource footprint. We are devoted to our humanitarian mission and look for new ways to make the world a better place. Velsera is an Equal Opportunity Employer: Velsera is proud to be an equal opportunity employer committed to providing employment opportunity regardless of sex, race, creed, colour, gender, religion, marital status, domestic partner status, age, national origin or ancestry. Show more Show less

Job title: R&D Data Modeling Manager Associate Location: Hyderabad Sanofi is a global life sciences company committed to improving access to healthcare and supporting the people we serve throughout the continuum of care. From prevention to treatment, Sanofi transforms scientific innovation into healthcare solutions, in human vaccines, rare diseases, multiple sclerosis, oncology, immunology, infectious diseases, diabetes and cardiovascular solutions and consumer healthcare. More than 110,000 people in over 100 countries at Sanofi are dedicated to making a difference in patients’ daily lives, wherever they live and enabling them to enjoy a healthier life. As a company with a global vision of drug development and a highly regarded corporate culture, Sanofi is recognized as one of the best pharmaceutical companies in the world and is pioneering the application of Artificial Intelligence (AI) with a strong commitment to developing advanced data standards to increase reusability & interoperability and thus accelerate impact on global health. The R&D Data Office serves as a cornerstone of this effort. Our team is responsible for cross-R&D data strategy, governance, and management. We partner with Business and Digital and drive data needs across priority and transformative initiatives across R&D. Team members serve as advisors, leaders, and educators to colleagues and data professionals across the R&D value chain. As an integral team member, you will be responsible for defining how R&D's structured, semi-structured and unstructured data will be stored, consumed, integrated / shared and reported by different end users such as scientists, clinicians, and more. You will also be pivotal in developing sustainable mechanisms for ensuring data are FAIR (findable, accessible, interoperable, and reusable). Position Summary The primary responsibility of this position is to support semantic integration and data harmonization across pharmaceutical R&D functions. In this role, you will design and implement ontologies and controlled vocabularies that enable interoperability of scientific, clinical, and operational data. Your work will be critical in accelerating discovery, improving data reuse, and enhancing insights across the drug development lifecycle. Main Responsibilities Develop, maintain, and govern ontologies and semantic models for key pharmaceutical domains, including preclinical, clinical, regulatory, and translational research Design and implement controlled vocabularies and taxonomies to standardize terminology across experimental data, clinical trials, biomarkers, compounds, and regulatory documentation Collaborate with cross-functional teams including chemists, biologists, pharmacologists, data scientists, and IT architects to align semantic models with scientific workflows and data standards Map internal data sources to public ontologies and standards to ensure FAIR (Findable, Accessible, Interoperable, Reusable) data principles Leverage semantic web technologies and ontology tools to build knowledge representation frameworks Participate in ontology alignment, reasoning, and validation processes to ensure quality and logical consistency Document semantic assets, relationships, and governance policies to support internal education and external compliance Deliverables Domain-specific ontologies representing concepts such as drug discovery (e.g., compounds, targets, assays), preclinical and clinical studies, biomarkers, adverse events, pharmacokinetics / dynamics, mechanisms of action, and disease models built using OWL/RDF and aligned with public standards Controlled vocabularies & taxonomies for experimental conditions, cell lines, compound classes, endpoints, clinical trial protocols, etc. Semantic data models supporting the integration of heterogeneous data sources (e.g., lab systems, clinical trial data, external databases) Knowledge graphs or knowledge maps for semantic integration of structured data from internal R&D systems Mappings to public ontologies, standards, and external knowledge bases like: CDISC, MedDRA, LOINC, UMLS, SNOMED CT, RxNorm, UniProt, DrugBank, PubChem, NCBI Ontology documentation & governance artifacts, including ontology scope, design rationale, versioning documentation, and usage guidelines for internal stakeholders Validation reports and consistency checks, including outputs from reasoners or SHACL validation to ensure logical coherence and change impact assessments when modifying existing ontologies Training and stakeholder support materials: slide decks, workshops, and tutorials on using ontologies in data annotation, integration, and search Support for application developers embedding semantic layers About You Experience: 5+ years of experience in ontology engineering, data management, data analysis, data architecture, or another related field Proven experience in ontology engineering, Proven experience in ontology development within the biomedical or pharmaceutical domain Experience working with biomedical ontologies and standards (e.g., GO, BAO, EFO, ChEBI, NCBI Taxonomy, NCI Thesaurus, etc.) Familiarity with controlled vocabulary curation and knowledge graph construction. Demonstrated ability to understand end-to-end data use and business needs Knowledge and/or experience of Pharma R&D or life sciences data and data domains. Understanding of FAIR data principles, data governance, and metadata management Strong analytical problem-solving skills. Demonstrated strong attention to detail, quality, time management and customer focus Excellent written and oral communication skills. Strong networking, influencing, and negotiating skills and superior problem-solving skills Demonstrated willingness to make decisions and to take responsibility for such. Excellent interpersonal skills (team player) Knowledge and experience in ontology engineering and maintenance are required. Knowledge and experience with OWL, RDF, SKOS, and SPARQL Familiarity with ontology engineering tools (e.g., Protégé, CENtree, TopBraid Composer PoolParty), Familiarity with ontology engineering methodologies (e.g., NeOn, METHONTOLOGY, Uschold and King, Grüninger and Fox, etc.) Knowledge and experience in data modeling are highly desired. Experience with pharma R&D platforms, requirements gathering, system design, and validation/quality/compliance requirements Experience with hierarchical data models from conceptualization to implementation, bachelor’s in computer science, Information Science, Knowledge Engineering, or related; Masters or higher preferred Languages: English null Show more Show less