Computational And Systems Biology Intern Jobs

1+ years industry or postdoctoral experience is preferred

5+ years experience in processing, analyzing and modeling large biological datasets (e.g. genomic, transcriptomic) to answer key biological questions

Experience predicting and analyzing 2D RNA structures, including using chemical probing data (e.g. DMSMaPseq, SHAPEseq) to inform RNA structures

Advanced knowledge of statistics (frequentist and Bayesian) for analyzing complex, multidimensional data

Experience developing data processing, engineering and statistical analysis workflows using AWS services such as S3, EC2, ECS, AWS Batch, NextFlow

Foundational knowledge of machine learning and small molecule therapeutics is a plus

Extensive experience with high-performance scalable data-intensive distributed/cloud computing environments utilizing scientific workflow management systems ensuring data integrity and consistency

Strong analytical and problem-solving abilities, excellent communication and interpersonal skills

Strong programming skills (Python/R preferred) combined with proficiency in software engineering best practices (version control, documentation, deployment, unit/integration testing) (required)

Working knowledge of applying statistical modeling to draw robust conclusions from complex datasets

Implementation and maintenance of production-scale pipelines for the analysis of diverse sequencing data

Design and benchmarking of novel analysis pipelines for newly established assays and increasing reliability and throughput of existing systems

Experience writing NGS analysis pipelines

Experience developing ML models for analysis of CRISPR editing

Experience with CRISPR editing, base editing, or prime editing is preferred.

Exceptional oral and written communication skills

Benchling, Tableau, or nextflow experience is a plus.

Design and analyze large library screens for CRISPR editing events

Genomics domain knowledge or experience

Collaborate with scientists to translate scientific needs into technical requirements

Bachelor’s Degree with 3+ years of professional experience

Master’s Degree with 1+ years of professional experience

Extensive experience with Python and the python ecosystem

Knowledge about Unix-like operating systems

Deep knowledge in one or more areas of cancer biology gained through research, and familiarity with other hallmarks of oncogenesis

Extensive experience with scientific programming in Python and R, including expertise using numpy, scipy, bioconductor, and similar toolkits

Experience with transcriptomics (e.g., scRNA-seq) and/or imaging (e.g. digital histopathology)

Experience with spatial transcriptomics and/or proteomics

Experience working with diverse functional genomic assays (RNA/DNase/ATAC/ChIP-seq, etc)

Experience working with clinicians or wet lab biologists to evaluate and follow-up on computational findings

Up-to-date knowledge of machine learning and various neural network models and their pros and cons or different applications.

Working knowledge of structural optimization (e.g., shape/topology optimization).

Research and develop novel approaches to solving shape/topology optimization problems with mutli-physics objectives and constraints.

Develop viable solutions to scientific research problems, that can be executed within the span of internship (e.g., three months).

Develop high-quality and scalable code according to industry standards.

Contribute to conference or journal papers.

Agenus is Delighted to Provide you With a Comprehensive Benefits Plan, Including Some of the Following:

Highly competitive and inclusive medical, dental and vision coverage options

Flexible Spending Accounts for medical expenses and dependent care expenses

401k match and Financial Planning tools

We put the patient first

We are bold, and we are one

A masters degree and work experience in a computer science, computational biology, bioinformatics, systems biology or related field.

Computer programming experience, ideally including C, perl and python programming languages.

A doctoral degree and post-doctoral experience in computer science, computational biology, bioinformatics, systems biology or related field is preferred.

Analyze large biological data sets to build accurate predictive models of biological processes and publish original work.

Collaborate with internal and external researchers to analyze and interpret novel results using newly derived methods.

Contribute to ongoing projects in the group and successfully define and develop their own projects.

Excellent organizational and team skills and experience managing multiple assignments.

Strong applied technical skills and analytical problem-solving skills.

Good oral and written communication skills.

Experience conducting research independently and in teams.

Develop and refine methodologies to characterize aroma and mouthfeel properties of grapes and wines.

Establish relevance of chemical metrics by modeling their relationship to sensory and grape and wine quality attributes.

A PhD degree and considerable postdoctoral work experience in a computer science, computational biology, bioinformatics, systems biology or related field.

Computer programming experience, ideally including perl and/or python programming languages.

Excellent written and oral communication skills and the ability to communicate in English to a scientific audience.

Analyze large biological data sets to build accurate predictive models of biological processes and publish original work.

Collaborate with internal and external researchers to analyze and interpret novel results using newly derived methods.

Contribute to ongoing projects in the group and successfully define and develop their own projects.