Available Opportunities and Resources

Trainee opportunities with Frederick National Laboratory for Cancer Research

Frederick National Laboratory for Cancer Research (FNL) is offering the below three projects to Purdue Center for Cancer Research (PCCR) Member trainees. These projects are aimed at developing skills in machine learning, predictive computational models, drug development, and coding. Please contact Maggie Scully (Maggie.scully@nih.gov) with any questions.

They are also offering numerous other virtual summer opportunities that are open to us and other institutions, please visit this link for information on these positions and how to apply.

Please note: the deadline for applications is January 24th. If you are interested and qualified, however, you can contact Maggie Scully (Maggie.scully@nih.gov) for a brief extension.

Undergrads and graduate students with appropriate experience/coursework are encouraged to apply for all positions mentioned in this email. These positions are unpaid by FNL. However, undergraduates who are selected for these positions will be eligible to apply for support via our Summer Undergrad Research Award if they are working with a PCCR-affiliated PI. Similarly, graduate students in PCCR member labs may be eligible for some financial support from the PCCR if their application is supported by their PI.

1. Developing machine-learning enabled cardio toxicity and other predictive computational models from canine  trial and research data.

Utilize available canine data and develop predictive models for drug response and potential toxicity. Work closely with Accelerating Therapeutics for Opportunities in Medicine (ATOM) Consortiumdata scientists to create computational models using machine learning approaches to predict response and impact of molecules in these areas. Resources include available Purdue data sources as well as data available in the integrated canine data commons. Results from the experience will guide the development and use of future canine predictive models for use in ATOM. Expected deliverables include assessment of available data for suitability for developing predictive models, identification of data gaps and voids in model areas of interest, and initial development of predictive models using ATOM model pipeline (AMPL).

2. Creating an extended database of precomputed computational predictions using ATOM released models.

Utilize available released ATOM predictive models to develop baseline reference databases of computational predictions for molecular structures in publicly available databases. Work closely with ATOM data scientists to create database representations to describe models unambiguously, develop fixed representations and versions of models, running models on lists of molecular structures available in public databases, and capturing predicted values. As data are available, predictive values will be compared against available experimental data to develop assessments of areas of high accuracy predictions, low accuracy predictions and areas of unknown accuracy. Tools developed within ATOM and beyond will be utilized to assess correlation of accuracy across chemical space definitions. Deliverables include annotated ATOM models, database of predicted ATOM model properties, and assessments of predictive accuracy.

3. Developing interoperable representations between ATOM predictive models,CANDLE predictive models, and other public deep learning frameworks.

Work with ATOM and FNL computational and data scientists to develop and implement approaches for cross-use of AMPLdeveloped and CANDLE developed computational predictive models. Approaches include use of compatible representations, containers, as well as identifying and/or developing tools and utilities to transform common public representations. Standards for data representation will be incorporated for effective descriptions of data used as both input and results from machine learning predictive models. Models will be deployed within the Model and Data Clearinghouse (MoDaC). Deliverables include updated code within CANDLE and AMPL as required for cross-compatibility, development of translation utility software to transform from one representation to another, and approaches for use of models in transfer learning between CANDLE and AMPL environments. 

Postdoc position in cryo-EM

An NIH-funded postdoc position is available in the lab of Dr. Leifu Chang lab at the Department of Biological Sciences at Purdue University.

The lab combines cryo-EM and biochemical reconstitution approach to understand the molecular mechanism of large protein complexes, particularly those in cell cycle regulation and CRISPR-Cas systems. Refer to our recent publications for more details. (https://pubmed.ncbi.nlm.nih.gov/?term=leifu%20chang%20or%20lei%20fu%20chang&sort=date)

The lab has access to two Titan Krios electron microscopes, both equipped with K3 direct electron detectors, and a Talos F200C with a K2 detector. All the microscopes are located in the same building of the lab.

Candidates should have a Ph.D. degree (or equivalent) in biology, chemistry, physics or computer science. Experience in protein expression and purification using insect cells or mammalian cells will be an advantage. Experience in cryo-EM and image processing is desired but not essential.

To apply, please contact Dr. Leifu Chang via email (lchang18@purdue.edu).

 

Postdoc positions at FNLCR

Four postdoctoral positions are currently available at Frederick National Laboratory for Cancer Research. Check this link for more information about the positions and proper HR point of contact for each.

 

CPRIT TRIUMPH Postdoctoral Fellowships (open to internationals)

Also see the flyer and posting on Nature Careers. Contact: Khandan Keyomarsi, PhD (Program Director). Upcoming application deadlines: Dec 31, 2020, March 31, 2021, June 30, 2021 and Sept 20, 2021.

Training Opportunity in Transdisciplinary Research in Obesity and Cancer

We are taking applications for our 5th annual Transdisciplinary Research on Energetics and Cancer (TREC) Training Workshop for early career investigators (i.e., junior faculty and postdocs). 

The Workshop focuses on working with Fellows on developing grant applications related to obesity and cancer from a translational and transdisciplinary perspective. Basic scientists, clinician-scientists and population scientists are encouraged to apply.

Funded by the U.S. National Cancer Institute and led by Yale University’s Dr. Melinda Irwin with a Senior Advisory Board and an expert international faculty, this 5-day, in residence* annual Workshop includes networking and collaborative opportunities with Faculty who span an array of professional disciplines. Formal didactic learning is integrated with one-on-one dialog and small group discussions to enable fellows to learn from each other, from faculty, and to develop a TD network. 

The 5th annual course will be held June 20-25, 2021 at Water’s Edge Resort, Westbrook, CT, U.S.A*. Costs will be covered. 

We welcome Notifications of Intent to apply (simple, informal email to dlowry@fredhutch.org) by Dec 31, 2020 (soft due date).  Full applications are due no later than Friday, January 15, 2021 (firm).

For more detail and to apply, visit TRECTraining.yale.edu.   Questions:  contact Diana Lowry dlowry@fredhutch.org      

 *Travel contingent on safety allowances due to the COVID-19 pandemic.  If necessary, we will conduct the 2021 Workshop virtually via Zoom, June 20-25, 2021.  Decision will be made by April 1, 2021.

 

Short courses offered by NCI Awardee Skills Development Consortium (NASDC)

The goal of NASDC is to provide opportunities for current NCI K01, K07, K08, K22, K23, K25, R00, R21, or first R01-equivalent grantees (R01-equivalent grants are defined as activity codes DP1, DP2, DP5, R01, R23, R29, R37, R56, RF1, RL1, U01) who are also junior faculty (e.g., assistant professors, instructors, research scientists, or equivalent) to participate in educational opportunities that will enhance their skills in areas that are not traditionally part of research training programs, but are critical for maintaining successful, long-term, academic research careers. The areas initially identified include: cutting-edge techniques in cancer research and leadership, mentorship, coping and networking/collaboration skills. NASDC is funded by the National Cancer Institute of the National Institutes of Health, through Cooperative Agreements and offered at no cost to participants.

Applications are currently being accepted for the following educational short courses. For more detailed information about each of these courses, and to register, please visit nasdc.osu.edu.

 

Utah Advanced Course on Mentorship and Leadership on Cancer-Related Health Disparities

Kolawole Okuyemi, MD, PhD, and Mia Hashibe, PhD

University of Utah

Dates: February 16 - March 10, 2021 (M/T) and monthly webinars from March to July

Delivery Format: Online

 

The Cell and Gene Therapy Toolkit for Junior Faculty

Elizabeth Hexner, MD, Stephan Grupp, MD, PhD, and David Mankoff, MD, PhD

University of Pennsylvania/Children's Hospital of Philadelphia (CHOP)

Dates: February 19 - March 26, 2021 (Fridays)

Delivery Format: Online

 

Academic Career Skills: Leadership, Collaboration and Resilience

William Pirl, MD, MPH, and Jennifer Temel, MD

Dana Farber Cancer Institute (DFCI)/Massachusetts General Hospital Cancer Center (MGHCC)

Dates: February 24-26, 2021

Delivery Format: Online

 

MSK Immuno-Oncology for the Translational Researcher Short Course

Ushma Neill, PhD, and Jedd Wolchok, MD, PhD

Memorial Sloan Kettering Cancer Center

Dates: March 24-26, 2021

Delivery Format: Online