Duties: Participate in R&D projects across multiple sites for the design, development and validation of new sequencing products; Support the bioinformatics function within a product development team; Contribute to the design and development of a standardized automated testing infrastructure; Analyze, integrate, model and interpret experimental data; Develop, document, and maintain reusable programming code; Communicate and collaborate in cross-functional multi-site teams
Requirements: Masters/PhD in bioinformatics, computer science, data science, engineering, mathematics or equivalent; Strong programming skills and experience with at least one programming languages, such as Python, R, etc; Experience with data analysis and visualization of next-generation sequencing data and large datasets; Familiarity with common bioinformatics pipelines and data formats; Solid understanding of statistical and biological concepts

Duties: Analyse, integrate, model and interpret experimental data to drive the development of whole-transcriptome and whole-genome clinical tests for oncology in proof-of-concept studies; Contribute to the design and development of a standardized automated validation infrastructure for use within an ISO15189 medical testing laboratory; Develop, document, and maintain reusable bioinformatics analysis code; Work with large data sets to solve complex problems of analytical, computational, or integration-related topics; Support the participation to External Quality Assurance Schemes and inter-laboratory comparison activities; Communicate and collaborate in cross-functional multi-site teams
Requirements: Masters, Ph.D. or equivalent in Bioinformatics, Computational Biology or related field; Proficient in bioinformatic and analysis tools and packages, especially for Next Generation Sequencing (NGS) data; Experience in cancer genomics is preferred; Experience in working in an ISO-accredited laboratory is preferred; Proficient in either R or Python, comfortable with shell scripting and HPC, familiarity with git

Duties: Lead the development of novel deep learning for deciphering the human genetic code, diagnosing pathogenic genetic variants by combining information from detailed clinical phenotypes and medical records, protein structures, and genomic data; Lead scientific collaborations with Illumina’s academic, nonprofit, and industry partners, and lead a multidisciplinary team focused on achieving these aims; Publish and disseminate methods and findings and incorporate them into software products to the benefit of the wider genetics community
Requirements: MD or PhD in computer science, genetics, computational biology, or related field; Expert in deep learning, statistics, proteinomics and/or genomics; Possesses strong communication skills, with the ability to present complex scientific ideas to clinical, scientific, and industry audiences; Be willing to work in a fast paced, competitive environment, and hold a strong record of successful delivery of complex scientific projects and publications under tight timelines

Duties: Candidates are invited to apply for a tenured professorship in the field of theory. The appointment is expected to begin on July 1, 2022. The tenured professor will be responsible for teaching at the undergraduate and graduate levels. We are seeking candidates who have an outstanding research record and a strong commitment to undergraduate and graduate teaching
Requirements: Doctorate required by expected start date

Duties: Work with small teams on national security problems, collaborating with the top academics in the domain of interest; Design and implement software solutions using the latest open-source software; test and evaluate the produced solutions and validate their capabilities against the customer needs; Participate in collaborative evaluations that assess performance against the state of the art; Support the program lead in preparing presentations and writeups that describe the uniqueness of the approach; Write and present conference papers about your work at peer-reviewed venues
Requirements: Typically requires BS with 5+ years, or MS with 3+ years, or PhD with 0-3 years; Degrees in Computer Science/Engineering, Mathematics, and other related fields are all welcome; Demonstrated experience in ML technologies such as Natural Language Processing, Reinforcement Learning, Complex Systems, etc; Proven ability to carry out a research project from idea to design, implementation, testing, and publication

Duties: Lead research direction on projects investigating diverse fields such as Information Management, Human Language Technologies, Data Analytics, Machine Intelligence and Autonomy, Planning and Estimation; Propose new research in machine learning applications to advance the state of the art; Build relationships with government program managers based on mutual respect for technological depth and creativity; Capture new business from new and existing customers by leveraging the strength of BBN expertise and capabilities
Requirements: Typically requires BS with minimum of 12 years of experience or an advanced degree and minimum of 10 years; Degrees in Computer Science, Computer Engineering, Computational Linguistics, Electrical Engineering, and other related fields are all welcome; Proven ability to produce technical artifacts in the form of publications in peer reviewed venues, or presentations to external customers and other stakeholders; Proven ability to carry out a research project from idea to design, implementation, testing, and publication

Duties: Participate in implementation and evaluation of leading-edge machine learning methods related to cancer immunotherapy; Explore large-scale immunological datasets, including genomic, transcriptomic, mass spectrometry, and structural data, to derive and integrate orthogonal contributors of effective immunotherapy design; Stay abreast of scientific findings and technological developments and continuously improve computational methodology; Maintain detailed documentation of data analysis methods and results; Present findings and participate in cross-function team meetings
Requirements: MS degree in Computational Biology, Bioinformatics, Computer Science, or a related field; Strong track record in machine learning algorithm development, preferably with applications in immunology, genomics, or personalized medicine; Proficiency in handling and interpreting large-scale biological datasets, including genomic and proteomic data; Strong programming skills in Python/R and with ML frameworks (e.g. PyTorch)

Duties: Work effectively in cross-functional teams and provide computational biology expertise to advance drug discovery for neuroinflammation and neurodegeneration; Analyze and integrate multi-omics data to identify novel therapeutic targets, review and validate therapeutic hypotheses, better understand disease mechanisms and causal pathways, and inform translational medicine strategies; Apply machine learning to the rich multi-level data (genetics, multi-omics, neuroimaging, fluid biomarkers, and clinical data) for target discovery, indication prioritization, and biomarker development
Requirements: Ph.D. in Computational Biology, Neuroscience, Statistics, Computer Science, or a related discipline; 5+ years of relevant research experience in applying advanced computational biology to solving biomedical problems; Extensive experience in analyzing multi-omics data (e.g., genetics, bulk RNA-seq, single-cell RNA-seq, spatial omics, proteomics, etc.) for biomedical research; Strong background and knowledge in human biology and/or medicine, especially neuroscience and related diseases

Duties: Conceiving of and conducting independent ML research, motivated by scientific milestones important to our team; Collaborating with colleagues across Flagship to apply our research to proprietary biological data and processes; Working with our ML Engineers to scale and interpret experiments
Requirements: PhD or MSc in a relevant field such as machine learning, computer science, math, physics etc. or equivalent practical experience; Significant deep learning experience relevant for position. Examples include geometric neural networks, generative modeling, representation learning, biological foundation models, multi-agent systems and reinforcement learning

Duties: Design, implement and evaluate leading-edge machine learning methods related to cancer immunotherapy; Explore large-scale immunological datasets, including genomic, transcriptomic, mass spectrometry, and structural data, to derive and integrate orthogonal contributors of effective immunotherapy design; Stay abreast of scientific findings and technological developments and continuously improve computational methodology; Maintain detailed documentation of data analysis methods and results; Present findings and participate in cross-function team meetings
Requirements: PhD degree in Computational Biology, Bioinformatics, Computer Science, or a related field + 2 years of relevant experience, or MS degree + 5 years of relevant experience; Strong track record in machine learning algorithm development, preferably with applications in immunology, genomics, or personalized medicine; Proficiency in handling and interpreting large-scale biological datasets, including genomic and proteomic data; Strong programming skills in Python/R and with ML frameworks (e.g. PyTorch)

Duties: Fine-tune, scale and deploy large language models over scientific and patent literature for knowledge extraction in materials synthesis and performance; Utilize and develop new prompt engineering strategies in the materials domain; Use LLM-backed agents for lab orchestration, design of experimental assays, and optimization of process parameters for materials synthesis and testing; Contribute to a digital platform that can continually finetune models as more data becomes available; Continually cultivate scientific/technical expertise through critical review of ML literature, attending conferences, writing publications, and developing relationships with key opinion leaders; Work with the computational team to identify materials design pathways that target desired functional properties and their synthesis
Requirements: PhD in Computer Science, Applied Mathematics, quantitative disciplines with strong focus in ML, or related field; Experience using a cloud computing service to reduce runtime to train and evaluate deep learning models; Coding experience with large language models (e.g. GPT or other autoregressive LLMs); Strong experience with prompt engineering; Hands-on experience implementing, deploying, evaluating, fine-tuning and hyperparameter-tuning deep learning models at scale; Experience in machine learning strategies like lifelong learning, online learning, incremental learning

Duties: Serve as the biostatistician in clinical development teams responsible for all clinical study biostatistics deliverables with high quality and on time; Responsible to bring innovative statistical thinking and operational excellence to help drive applications of state-of-art statistical methods that increase the probability of successes for clinical development programs; Develop statistical sections of protocols, statistical analysis plans, and key specifications for statistical programming implementation of analyses; Plan, manage, and track biostatistics activities, timelines, and resources and assure operational excellence; Contribute to SOPs and/or Work Instructions related to biostatistics practices
Requirements: PhD in statistics (or equivalent degree) with 4+ years or master with 7+ years of relevant working experience in Biotech, Pharma, Regulatory agencies, or Clinical Research Organizations; Excellent statistical knowledge with the ability of applying the knowledge to solve scientific and clinical problems; Working knowledge of relevant ICH guidelines, US, EU and other regions’ regulations; Experience working on oncology, vaccine/infectious disease and rare disease clinical studies and regulatory interactions are preferred; Experience working with CROs, vendors, and relationship management

Duties: Lead computational investigations into the impact of novel formulations on biology. Partner with cross-functional teams to develop principled design of experiment strategies (e.g., adaptive designs, optimal designs), statistical models and computational methods; Design and carry out data analysis strategies (normalization, statistical inference) for biophysical measurements and bioassays (e.g., ELISA, amplicon-seq, mass spec); Explore and build novel statistical models or machine learning methods to advance our platform technology; Collaborate with bioinformatic engineers and develop tools to enable data democratization; Independently manage multiple concurrent, fast-paced projects across Moderna’s research ecosystem. Partner with wet-lab and dry-lab scientists
Requirements: Ph.D. in Statistics, Biostatistics, or related quantitative discipline; 5+ years of relevant academia or industry experience (post PhD) is required; Establish records working with cross-functional teams (e.g., publications, work experiences); Strong coding skills with R and Python

Duties: Leader in bringing innovative statistical thinking and methods to help drive applications of suit-for-purpose statistical methods that enhance the probability of successes for clinical development programs; Collaborate with internal and external stakeholders to ensure effective quantitative approaches are applied to the collection and analysis of a wide variety of data types; Develop statistical sections of clinical development plans, protocols, statistical analysis plans, and key specifications for statistical programming implementation of analyses; Plan, manage, and track biostatistics activities, timelines, and resources and assure operational excellence
Requirements: PhD in statistics (or equivalent degree) with 6+ years or master with 9+ years of relevant working experience in Biotech, Pharma, Regulatory agencies, or Clinical Research Organizations; Excellent statistical knowledge with the ability of applying the knowledge to solve scientific and clinical problems; Working knowledge of relevant ICH guidelines, US, EU and other regions’ regulations; Experience working on oncology, vaccine/infectious disease and rare disease clinical studies and regulatory interactions are preferred

Duties: Building scalable machine learning pipelines, including efficient parallelization and use of GPUs; Designing and coding data processing pipelines, ownership of company-wide data platform; Working closely with Platform Development and Biology teams to automate a tight design-build-test cycle for ML generated small molecules; Working in a collaborative CI/CD software development environment, including use of git, participating in code reviews, and independent development of robust code; Working within an entrepreneurial, collaborative, and interdisciplinary team to actively contribute to creating, shaping, and executing the vision of the company
Requirements: Undergraduate or Master's degree in bioinformatics, computer science, mathematics, physics or related field and 4+ years of experience is required; Experience with MLOps practices and tools including version control, automated testing, and CI/CD; Proficient in Python and experience in using deep learning libraries (i.e. PyTorch); Experience with cloud computing (i.e. AWS), database scale-out (e.g. distributed postgresql), and data pipelining tools (i.e. Nextflow, Airflow); Experience with Slurm or other on-site HPC cluster solutions

Duties: Candidates are invited to apply for a tenured professorship in all fields of chemistry. The appointment is expected to begin on January 1, 2024. The tenured professor will be responsible for teaching at the undergraduate and graduate levels. We are seeking candidates who have an outstanding research record and a strong commitment to undergraduate and graduate teaching
Requirements: Doctorate required by expected start date

Duties: The Lewis Lab seeks a talented and enthusiastic Research Fellow to help in the development and application of novel 3D bioprinting methods for disease modeling and therapeutic tissues. The ideal candidate will report to the Principal Investigator in the Lewis Research Group and work closely with a senior postdoctoral research associate. This is a 1-year position with an opportunity to be extended
Requirements: B.S. in Biomedical Engineering, Chemical Engineering, Mechanical Engineering, Materials Science, Biology, Biochemistry, Immunology, or related discipline is required

Duties: Regular mentoring of Ph.D. and postdoctoral scientists carrying out microbiome research, which includes bioinformatic screening for microbiome-derived bioactives, microbial and mammalian cellular growth and phenotyping assays, and gnotobiotic mouse screens
Requirements: Ph.D. in Molecular Biology, Computational Biology, or related fields, with advanced research skills and at least 5 years of related experience. Combination of molecular biology and computational expertise preferred

Duties: Design, implement, and operate robust, scalable genomic data processing pipelines using Nextflow on AWS; Manage pipeline results using big data technologies (e.g. distributed databases); Manage pipeline-related assets to ensure that they are findable, accessible, interoperable and reusable; Apply best practices for version control, testing, and documentation; Ensure data quality and integrity by implementing and maintaining rigorous quality control and data validation procedures; Collaborate closely with platform scientists, data scientists, and data engineers to solve complex data processing and analysis challenges
Requirements: MSc or PhD or equivalent in bioinformatics, computational biology, computer science, or similar discipline; 3-plus years of post-graduate or industry experience developing high-throughput bioinformatic data processing pipelines; Experience in NGS mapping, variant calling and variant analysis preferred; Experience in bioinformatics workflow frameworks (NextFlow), version control systems (Git), Cloud (AWS preferred), and containers (Docker preferred); High level of proficiency in Python or equivalent and Linux

Duties: The successful candidate will work with Drs. Curtis Huttenhower and Wendy Garrett on overall scientific coordination for the Harvard Chan Microbiome in Public Health Center. This individual will be responsible for high-level scientific planning, reporting, outreach, and mentoring for the project, working with both computational and experimental scientists in multiple labs that are part of the Center. There will be ample opportunities to plan new projects; prepare presentations, proposals, and manuscripts with the Center and affiliated PIs, students, and postdoctoral fellows; funding reporting; and coordinate with the broader HCMPH community
Requirements: Ph.D. in Molecular Biology, Computational Biology, or related fields, with advanced research skills and at least 5 years of related experience. Combination of molecular biology and computational expertise preferred

Duties: A Postdoctoral Research Fellow or Research Associate position in biostatistics and biomedical informatics is available at Harvard T.H. Chan School of Public Health. The positions involve developing and applying statistical and computational methods for analysis of electronic health records ( EHR ) data including narrative data extracted via natural language processing, codified phenotype data as well as large scale genomic measurements. We seek an individual with strong statistical and computing backgrounds and who has expertise in statistical and machine learning methods for big data. The work will involve development and application of statistical and informatics methods and algorithm for analyzing EHR data
Requirements: Ph.D. in a quantitative field, e.g., statistics or biostatistics, computer sciences, strong quantitative research background, statistical and programming proficiency, as well as good written and oral communication skills; for the Research Associate position two years of postdoctoral experience is preferred

Duties: We are seeking a candidate with expertise in computational and systems biology to work as part of a multidisciplinary team developing methods relevant to the study of genetics, gene regulatory networks, and the use of quantitative imaging data as biomarkers. Our goal is to use these methods to better understand the development, progression, and response to therapy
Requirements: A PhD in computational biology, biostatistics, applied mathematics, physics, biology, or related fields and demonstrated skill in methods and software development and the analysis of biological data are required

Duties: The Lewis Lab is seeking a postdoctoral fellow with expertise in one or more of the following areas: nanoparticle synthesis, colloidal science, rheology, or granular media. The successful candidate will join a multidisciplinary team of researchers supported under a new ARO MURI award. The goal of this project is to develop a fundamental understanding of the transient yielding and printing behavior of highly heterogeneous particle systems
Requirements: Candidates must have a Doctorate degree in Chemistry, Materials Science, Chemical Engineering, or Applied Physics by the time the appointment begins

Duties: Accountable for the leadership, development, and execution of the Epidemiology strategy for EBV vaccines; Provide epidemiologic input to the product development, clinical, safety, and regulatory affairs teams, contributing to the integrated evidence generation plans for EBV; Design and execute pre- and potentially post-marketing epidemiology plans, including burden of disease studies, literature reviews and gap analyses, mathematical modeling, and post-marketing safety, effectiveness, and impact studies, as needed
Requirements: PhD in Epidemiology. Strong preference given to candidates with previous experience in vaccine research or development and for candidates with experience with EBV; ≥10 years’ experience in an industry setting, preferably in vaccines or a related therapeutic area

Duties: Develop the vision and strategic plan for FL94’s machine learning platform, driving novel discoveries in small molecule chemistry; Build and lead the data science team translating small molecule and proteomic drug discovery challenges into breakthroughs via deep learning applied to computational chemistry; Own the philosophy and strategy behind core machine learning technology and applications; Develop a robust data portal that will enable the application of generative models to proprietary chemoproteomics data; Define team mission and propose org structure and interaction model to ensure for successful execution
Requirements: A proven leader with a Ph.D. in machine learning, statistics, computer science, mathematical modeling, operations research, or related field computational chemistry, or other highly-technical fields from a recognized higher-education establishment; >3-10 years of experience in the area of computational science and artificial intelligence with track record and experience track record of solving real-world problems. Ideally candidates would have deep experience in small molecule drug discovery, talented candidates without such experience will also be considered