Summer Research Interns, Center for Computational Biology

Description

Summer Research Assistant/Associate, Center for Computational Biology

The Center for Computational Biology (CCB) of the Simons Foundation’s Flatiron Institute aims to advance the understanding of fundamental and historically challenging biological processes by developing theory, innovative modeling tools for large-scale biophysical simulations, and computational frameworks for analyzing increasingly large and complex experimental datasets. Living systems are built hierarchically; as such, CCB’s research activities span several scales of biological organization, bridging the gap between microscopic detail and large-scale behaviors, and providing natural continuity between our groups’ efforts. CCB currently comprises more than 45 research and data scientists at career stages from recent Ph.D. graduates through senior scientists, as well as visiting scientists, guest researchers, graduate students, interns, and administrative support staff. For a full description of CCB research areas and scientific staff, please see our website. 

The Center for Computational Biology (CCB) of the Simons Foundation’s Flatiron Institute invites applications for our Summer Research Assistant (undergraduate-level interns) and Summer Research Associate (graduate-level interns) internship position(s). 

POSITION SUMMARY

Our seasonal, full-time research interns working will work in one or more of our active areas of research, which include: 

• Biological Transport Networks: The Biological Transport Networks group focuses on understanding transport mechanisms in living organisms. Our primary interests lie in modeling the function and development of vascular networks across multiple scales, and in understanding the dynamics of neuronal growth. We utilize advanced computational and theoretical techniques, including large-scale network simulations and methods from topological data analysis, to address a wide range of problems. Examples of our work include modeling the circulatory systems of developing embryos, exploring how intracellular transport influences neuronal development, quantifying extensive datasets of brain microvasculature, and understanding the effects of nonlinearities within vascular networks.

• Biomolecular Design: The Biomolecular Design team applies the principles that underlie the function of natural biological macromolecules to design artificial and synthetic macromolecules with new, desired functions.  This serves as the ultimate test of our understanding of macromolecular folding and function, while simultaneously giving rise to useful molecules for medicine, materials, or manufacturing. The team focuses on both the development and application of computational tools to our current focus areas; the design of cyclic peptides, peptoid-foldamers, hinge-proteins, and catalysts. During the summer internship, interns can expect to work on one of the many design application projects based on their interest as well as project availability using various state of the art simulation, machine learning, or quantum computing tools.

• Biophysical Modeling: The Biophysical Modeling group focuses on the modeling and simulation of complex systems that arise in biology and soft condensed matter physics. Areas of interest include the dynamics of complex and active materials, and aspects of collective behavior and self-organization in both natural systems (e.g., inside the cell) and synthetic ones. To address these, often in close collaboration with experimental collaborators, we build numerical and theoretical models from the ground up, revealing how the known mechanics of individual components give rise to collective behavior. 

• Developmental Dynamics: The Developmental Dynamics group combines experiments, theory and computing to elucidate the contributions of encoded genomic instructions and self-organizing physical mechanisms to embryonic development. Its theoretical and computational work is designed to integrate and abstract rapidly accumulating heterogeneous datasets, to propose critical tests of multiscale regulatory mechanisms, and to guide our own genetic and imaging experiments. The group’s research is organized around three main themes: the mechanistic modeling of pattern formation and morphogenesis; the synthesis and decomposition of developmental trajectories; and the modeling of human developmental defects.

• Genomics:The Genomics group  works to interpret genomes and distill the immensely complex networks that form the foundation of human biology and disease, through accurate machine learning models.   Current areas of interest include developing deep learning approaches for genome interpretation; development of methods for multi-omic data analysis and integration with phenotypic and clinical data;  and machine learning approaches for network modeling and regulatory module detection.  These and other methods are developed in tight collaboration with experimental biologists, biomedical scientists, and clinicians and are applied to specific biological problems, both fundamental and biomedical.

• Structural and Molecular Biophysics: The Structural and Molecular Biophysics team, a collaborative effort between CCB and the Center for Computational Mathematics (CCM)  uses computational tools to study biological macromolecules, running long timescale molecular simulations and developing statistical analysis and machine learning tools to better capture the dynamics of these molecules and understand their biological function. Areas of interest include in particular statistical mechanics, membrane protein structural biology, protein modeling with flexibility, cryo-electron microscopy, thermodynamics, modeling the effect of mutations, and intrinsically disordered proteins.  

• Computer Vision & Machine Learning: Recent work involves instance segmentation, tracking and lineage construction of pre-implantation mouse embryogenesis and extending this to other organisms. This has included extensive benchmarking of segmentation approaches, developing a generalized approach to detect mitotic events and optimizing track associations using simulated annealing.

Interns will be assigned a primary mentor and research group within the center, and will participate in research group’s meetings and seminars. They will also participate in other center- and Flatiron Institute-wide activities such as guest lectures, training on use of the Institute’s robust scientific computing resources, and intern social activities.

This is a paid, full-time internship that will run generally from late May through mid-August, and will take place in our New York City offices. CCB will reimburse travel to New York City, and housing will be available for interns based outside of the five boroughs of New York City. CCB interns are invited to participate as full members of the CCB and Flatiron communities during their internship.

Visit the Flatiron Institute career page to learn more.

Qualifications

Education

• Applicants must be currently pursuing or recently completed a bachelor’s, master’s, or be only in the initial stages of their PhD program (first 1-2 years) in applied mathematics, statistics, computational biology, biophysics, computer science, engineering, mathematics physics, or related disciplines. 

Related Skills & Experience

• Demonstrated abilities in mathematical modeling, biophysical analysis and/or scientific computation, scientific software and algorithm development, data analysis and inference, and image analysis

• Ability to do original and outstanding research in computational biology

• Ability to work well in an interdisciplinary environment, and to collaborate with experimentalists

• Strong oral and written communication, data documentation, and presentation skills

• Excellent collaborative and interpersonal skills.

Application Instructions

Applications must include:

• Resume or CV

• Transcript (unofficial or official)

• Cover letter (1 page max, essay and/or bullet points), which addresses the following questions

• What are your qualifications for computational biology research?

• Why are you interested in computational biology?

• What are some project directions you could be interested in exploring?

DEADLINE

Applications for Summer 2025 internships  will be reviewed beginning January 2024, and will be considered on a rolling basis until the positions are filled. For full consideration, applicants are strongly encouraged to submit their complete applications by January 17, 2025.  

COMPENSATION

• Interns at the Research Assistant (undergraduate) level will earn $20/hour

• Interns at the Research Associate (graduate) level will earn $25/hour

• Interns at the Pre-Doctoral (2 years of PhD-level studies, started thesis and actively working PIs) will earn $28/hour.

Equal Employment Opportunity Statement

SIMONS FOUNDATION'S DIVERSITY COMMITMENT

Many of the greatest ideas and discoveries come from a diverse mix of minds, backgrounds and experiences, and we are committed to cultivating an inclusive work environment. The Simons Foundation actively seeks a diverse applicant pool and encourages candidates of all backgrounds to apply. We provide equal opportunities to all employees and applicants for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, genetic disposition, neurodiversity, disability, veteran status, or any other protected category under federal, state and local law.